Geo(spatial) Health Investigation of Rotavirus in an Endemic Region: Hydroclimatic Influences and Epidemiology of Rotavirus in Bangladesh

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Akanda, A. S.; Jutla, A.; Colwell, R. R.

2016-12-01

Rotavirus is the leading cause of severe dehydrating diarrhea among children under 5. Over 80% of the approximate half a million child deaths every year occur in South Asia and sub-Saharan Africa alone. Although less explored than cholera as a climate driven and influenced global health problem, recent studies have showed that the disease shown strong seasonality and spatio-temporal variability depending on regional hydroclimatic and local environmental conditions. Understanding the epidemiology of this disease, especially the spatio-temporal incidence patterns with respect to environmental factors is vitally important to allow for identification of "hotspots", preventative preparations, and vaccination strategies to improve wellbeing of the vulnerable populations. With climate change, spatio-temporal signatures and footprints of the disease are changing along with increasing burden. However, a robust understanding of the relationships between rotavirus epidemiology and hydroclimatic drivers is yet to be developed. In this study, we evaluate the seasonality and epidemiologic characteristics of rotavirous infection and its spatio-temporal incidence patterns with respect to regional hydroclimatic variables and their extremes in an endemic region in South Asia. Hospital-based surveillance data from different geographic locations allowed us to explore the detailed spatial and temporal characteristics of rotavirus propagation under the influence of climate variables in both coastal and inland areas. The rotavirus transmission patterns show two peaks in a year in the capital city of Dhaka, where winter season (highest in January) shows a high peak and the July-August monsoon season shows a smaller peak. Correlation with climate variables revealed that minimum temperature has strong influence on the winter season outbreak, while rainfall extremes show a strong positive association with the secondary monsoon peak. Spatial analysis also revealed that humidity and soil wetness may influence the timing as drier areas experience earlier outbreaks than wetter areas. Accurate understanding of rotavirus propagation with respect to hydroclimatic and environmental variability can be utilized to establish global surveillance and forecast imminent risk of diarrheal outbreaks in vulnerable regions.

[Spatio-temporal analysis of the biophysical and ecological conditions of Triatoma dimidiata (Hemiptera: Reduviidae: Triatominae) in the northeast region of Colombia].

PubMed

Badel-Mogollón, Jaime; Rodríguez-Figueroa, Laura; Parra-Henao, Gabriel

2017-03-29

Due to the lack of information regarding biophysical and spatio-temporal conditions (hydrometheorologic and vegetal coverage density) in areas with Triatoma dimidiata in the Colombian departments of Santander and Boyacá, there is a need to elucidate the association patterns of these variables to determine the distribution and control of this species. To make a spatio-temporal analysis of biophysical variables related to the distribution of T. dimidiate observed in the northeast region of Colombia. We used the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) data bases registering vector presence and hydrometheorologic data. We studied the variables of environmental temperature, relative humidity, rainfall and vegetal coverage density at regional and local levels, and we conducted spatial geostatistic, descriptive statistical and Fourier temporal series analyses. Temperatures two meters above the ground and on covered surface ranged from 14,5°C to 18,8°C in the areas with the higher density of T. dimidiata. The environmental temperature fluctuated between 30 and 32°C. Vegetal coverage density and rainfall showed patterns of annual and biannual peaks. Relative humidity values fluctuated from 66,8 to 85,1%. Surface temperature and soil coverage were the variables that better explained the life cycle of T. dimidiata in the area. High relative humidity promoted the seek of shelters and an increase of the geographic distribution in the annual and biannual peaks of regional rainfall. The ecologic and anthropic conditions suggest that T. dimidiata is a highly resilient species.

Variability of tornado occurrence over the continental United States since 1950

NASA Astrophysics Data System (ADS)

Guo, Li; Wang, Kaicun; Bluestein, Howard B.

2016-06-01

The United States experiences the most tornadoes of any country in the world. Given the catastrophic impact of tornadoes, concern has arisen regarding the variation in climatology of U.S. tornadoes under the changing climate. A recent study claimed that the temporal variability of tornado occurrence over the continental U.S. has increased since the 1970s. However, that study ignored the highly regionalized climatology of U.S. tornadoes. To address this issue, we examined the long-term trend of tornado temporal variability in each continental U.S. state. Based on the 64 year tornado records (1950-2013), we found that the trends in tornado temporal variability varied across the U.S., with only one third of the continental area or three out of 10 contiguous states (mostly from the Great Plains and Southeast, but where the frequency of occurrence of tornadoes is greater) displaying a significantly increasing trend. The other two-thirds area, where 60% of the U.S. tornadoes were reported (but the frequency of occurrence of tornadoes is less), however, showed a decreasing or a near-zero trend in tornado temporal variability. Furthermore, unlike the temporal variability alone, the combined spatial-temporal variability of U.S. tornado occurrence has remained nearly constant since 1950. Such detailed information on the climatological variability of U.S. tornadoes refines the claim of previous study and can be helpful for local mitigation efforts toward future tornado risks.

Spatial and temporal variability in rates of landsliding in seismically active mountain ranges

NASA Astrophysics Data System (ADS)

Parker, R.; Petley, D.; Rosser, N.; Densmore, A.; Gunasekera, R.; Brain, M.

2012-04-01

Where earthquake and precipitation driven disasters occur in steep, mountainous regions, landslides often account for a large proportion of the associated damage and losses. This research addresses spatial and temporal variability in rates of landslide occurrence in seismically active mountain ranges as a step towards developing better regional scale prediction of losses in such events. In the first part of this paper we attempt to explain reductively the variability in spatial rates of landslide occurrence, using data from five major earthquakes. This is achieved by fitting a regression-based conditional probability model to spatial probabilities of landslide occurrence, using as predictor variables proxies for spatial patterns of seismic ground motion and modelled hillslope stability. A combined model for all earthquakes performs well in hindcasting spatial probabilities of landslide occurrence as a function of readily-attainable spatial variables. We present validation of the model and demonstrate the extent to which it may be applied globally to derive landslide probabilities for future earthquakes. In part two we examine the temporal behaviour of rates of landslide occurrence. This is achieved through numerical modelling to simulate the behaviour of a hypothetical landscape. The model landscape is composed of hillslopes that continually weaken, fail and reset in response to temporally-discrete forcing events that represent earthquakes. Hillslopes with different geometries require different amounts of weakening to fail, such that they fail and reset at different temporal rates. Our results suggest that probabilities of landslide occurrence are not temporally constant, but rather vary with time, irrespective of changes in forcing event magnitudes or environmental conditions. Various parameters influencing the magnitude and temporal patterns of this variability are identified, highlighting areas where future research is needed. This model has important implications for landslide hazard and risk analysis in mountain areas as existing techniques usually assume that susceptibility to failure does not change with time.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

Dose reduction in fluoroscopic interventions using a combination of a region of interest (ROI) x-ray attenuator and spatially different, temporally variable temporal filtering

NASA Astrophysics Data System (ADS)

Swetadri Vasan, S. N.; Pope, Liza; Ionita, Ciprian N.; Titus, A. H.; Bednarek, D. R.; Rudin, S.

2013-03-01

A novel dose reduction technique for fluoroscopic interventions involving a combination of a material x-ray region of interest (ROI) attenuator and spatially different, temporally variable ROI temporal recursive filter, was used to guide the catheter to the ROI in three live animal studies, two involving rabbits and one involving a sheep. In the two rabbit studies presented , a catheter was guided to the entrance of the carotid artery. With the added ROI attenuator the image under the high attenuation region is very noisy. By using temporal filtering with a filter weight of 0.6 on previous frames, the noise is reduced. In the sheep study the catheter was guided to the descending aorta of the animal. The sheep offered a relatively higher attenuation to the incident x-rays and thus a higher temporal filter weight of 0.8 on previous frames was used during the procedure to reduce the noise to levels acceptable by the interventionalist. The image sequences from both studies show that significant dose reduction of 5-6 times can be achieved with acceptable image quality outside the ROI by using the above mentioned technique. Even though the temporal filter weighting outside the ROI is higher, the consequent lag does not prevent perception of catheter movement.

A comprehensive overview of the spatial and temporal variability of apple bud dormancy release and blooming phenology in Western Europe

NASA Astrophysics Data System (ADS)

Legave, Jean Michel; Blanke, Michael; Christen, Danilo; Giovannini, Daniela; Mathieu, Vincent; Oger, Robert

2013-03-01

In the current context of global warming, an analysis is required of spatially-extensive and long-term blooming data in fruit trees to make up for insufficient information on regional-scale blooming changes and determinisms that are key to the phenological adaptation of these species. We therefore analysed blooming dates over long periods at climate-contrasted sites in Western Europe, focusing mainly on the Golden Delicious apple that is grown worldwide. On average, blooming advances were more pronounced in northern continental (10 days) than in western oceanic (6-7 days) regions, while the shortest advance was found on the Mediterranean coastline. Temporal trends toward blooming phase shortenings were also observed in continental regions. These regional differences in temporal variability across Western Europe resulted in a decrease in spatial variability, i.e. shorter time intervals between blooming dates in contrasted regions (8-10-day decrease for full bloom between Mediterranean and continental regions). Fitted sequential models were used to reproduce phenological changes. Marked trends toward shorter simulated durations of forcing period (bud growth from dormancy release to blooming) and high positive correlations between these durations and observed blooming dates support the notion that blooming advances and shortenings are mainly due to faster satisfaction of the heating requirement. However, trends toward later dormancy releases were also noted in oceanic and Mediterranean regions. This could tend toward blooming delays and explain the shorter advances in these regions despite similar or greater warming. The regional differences in simulated chilling and forcing periods were consistent with the regional differences in temperature increases.

Long-term variability of importance of brain regions in evolving epileptic brain networks

NASA Astrophysics Data System (ADS)

Geier, Christian; Lehnertz, Klaus

2017-04-01

We investigate the temporal and spatial variability of the importance of brain regions in evolving epileptic brain networks. We construct these networks from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients and use centrality indices to assess the importance of brain regions. Time-resolved indications of highest importance fluctuate over time to a greater or lesser extent, however, with some periodic temporal structure that can mostly be attributed to phenomena unrelated to the disease. In contrast, relevant aspects of the epileptic process contribute only marginally. Indications of highest importance also exhibit pronounced alternations between various brain regions that are of relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches. Nonetheless, these findings may guide new developments for individualized diagnosis, treatment, and control.

Climate and climate variability of the wind power resources in the Great Lakes region of the United States

Treesearch

X. Li; S. Zhong; X. Bian; W.E. Heilman

2010-01-01

The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution...

Temporally variable environments maintain more beta-diversity in Mediterranean landscapes

NASA Astrophysics Data System (ADS)

Martin, Beatriz; Ferrer, Miguel

2015-10-01

We examined the relationships between different environmental factors and the alpha and beta-diversity of terrestrial vertebrates (birds, mammals, amphibians and reptiles) in a Mediterranean region at the landscape level. We investigated whether the mechanisms underlying alpha and beta-diversity patterns are influenced by energy availability, habitat heterogeneity and temporal variability and if the drivers of the diversity patterns differed between both components of diversity. We defined alpha-diversity as synonym of species richness whereas beta-diversity was measured as distinctiveness. We evaluated a total of 13 different predictors using generalized linear mixed model (GLMM) analysis. Habitat spatial heterogeneity increased alpha-diversity, but contrastingly, it did not significantly affect beta-diversity among sites. Disturbed landscapes may show higher habitat spatial variation and higher alpha-diversity due to the contribution of highly generalist species that are wide-distributed and do not differ in composition (beta-diversity) among different sites within the region. Contrastingly, higher beta-diversity levels were negatively related to more stable sites in terms of temporal environmental variation. This negative relationship between environmental stability and beta-diversity levels is explained in terms of species adaptation to the local environmental conditions. Our study highlights the importance of temporal environmental variability in maintaining beta-diversity patterns under highly variable environmental conditions.

Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow

NASA Astrophysics Data System (ADS)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward R.

2017-04-01

The development of paleoclimate streamflow reconstructions in the conterminous United States (CONUS) has provided water resource managers with improved insights into multidecadal and centennial scale variability that cannot be reliably detected using shorter instrumental records. Paleoclimate streamflow reconstructions have largely focused on individual catchments limiting the ability to quantify variability across the CONUS. The Living Blended Drought Atlas (LBDA), a spatially and temporally complete 555 year long paleoclimate record of summer drought across the CONUS, provides an opportunity to reconstruct and characterize streamflow variability at a continental scale. We explore the validity of the first paleoreconstructions of streamflow that span the CONUS informed by the LBDA targeting a set of U.S. Geological Survey streamflow sites. The reconstructions are skillful under cross validation across most of the country, but the variance explained is generally low. Spatial and temporal structures of streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. Nine spatially coherent clusters are identified. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s) and 1950s droughts. Decadal-scale variability was detected in the late 1900s in the western U.S., however, similar modes of temporal variability were rarely present prior to the 1950s. The twentieth century featured longer wet spells and shorter dry spells compared with the preceding 450 years. Streamflows in the Pacific Northwest and Northeast are negatively correlated with the central U.S. suggesting the potential to mitigate some drought impacts by balancing economic activities and insurance pools across these regions during major droughts.

The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2010-01-01

Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

Temporal coherence among tropical coastal lagoons: a search for patterns and mechanisms.

PubMed

Caliman, A; Carneiro, L S; Santangelo, J M; Guariento, R D; Pires, A P F; Suhett, A L; Quesado, L B; Scofield, V; Fonte, E S; Lopes, P M; Sanches, L F; Azevedo, F D; Marinho, C C; Bozelli, R L; Esteves, F A; Farjalla, V F

2010-10-01

Temporal coherence (i.e., the degree of synchronicity of a given variable among ecological units within a predefined space) has been shown for several limnological features among temperate lakes, allowing predictions about the structure and function of ecosystems. However, there is little evidence of temporal coherence among tropical aquatic systems, where the climatic variability among seasons is less pronounced. Here, we used data from long-term monitoring of physical, chemical and biological variables to test the degree of temporal coherence among 18 tropical coastal lagoons. The water temperature and chlorophyll-a concentration had the highest and lowest temporal coherence among the lagoons, respectively, whereas the salinity and water colour had intermediate temporal coherence. The regional climactic factors were the main factors responsible for the coherence patterns in the water temperature and water colour, whereas the landscape position and morphometric characteristics explained much of the variation of the salinity and water colour among the lagoons. These results indicate that both local (lagoon morphometry) and regional (precipitation, air temperature) factors regulate the physical and chemical conditions of coastal lagoons by adjusting the terrestrial and marine subsidies at a landscape-scale. On the other hand, the chlorophyll-a concentration appears to be primarily regulated by specific local conditions resulting in a weak temporal coherence among the ecosystems. We concluded that temporal coherence in tropical ecosystems is possible, at least for some environmental features, and should be evaluated for other tropical ecosystems. Our results also reinforce that aquatic ecosystems should be studied more broadly to accomplish a full understanding of their structure and function.

Analysis of the historical precipitation in the South East Iberian Peninsula at different spatio-temporal scale. Study of the meteorological drought

NASA Astrophysics Data System (ADS)

Fernández-Chacón, Francisca; Pulido-Velazquez, David; Jiménez-Sánchez, Jorge; Luque-Espinar, Juan Antonio

2017-04-01

Precipitation is a fundamental climate variable that has a pronounced spatial and temporal variability on a global scale, as well as at regional and sub-regional scales. Due to its orographic complexity and its latitude the Iberian Peninsula (IP), located to the west of the Mediterranean Basin between the Atlantic Ocean and the Mediterranean Sea, has a complex climate. Over the peninsula there are strong north-south and east-west gradients, as a consequence of the different low-frequency atmospheric patterns, and he overlap of these over the year will be determinants in the variability of climatic variables. In the southeast of the Iberian Peninsula dominates a dry Mediterranean climate, the precipitation is characterized as being an intermittent and discontinuous variable. In this research information coming from the Spain02 v4 database was used to study the South East (SE) IP for the 1971-2010 period with a spatial resolution of 0.11 x 0.11. We analysed precipitation at different time scale (daily, monthly, seasonal, annual,…) to study the spatial distribution and temporal tendencies. The high spatial, intra-annual and inter-annual climatic variability observed makes it necessary to propose a climatic regionalization. In addition, for the identified areas and subareas of homogeneous climate we have analysed the evolution of the meteorological drought for the same period at different time scales. The standardized precipitation index has been used at 12, 24 and 48 month temporal scale. The climatic complexity of the area determines a high variability in the drought characteristics, duration, intensity and frequency in the different climatic areas. This research has been supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 project for the data provided for this study.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Anterior Temporal Lobe Morphometry Predicts Categorization Ability.

PubMed

Garcin, Béatrice; Urbanski, Marika; Thiebaut de Schotten, Michel; Levy, Richard; Volle, Emmanuelle

2018-01-01

Categorization is the mental operation by which the brain classifies objects and events. It is classically assessed using semantic and non-semantic matching or sorting tasks. These tasks show a high variability in performance across healthy controls and the cerebral bases supporting this variability remain unknown. In this study we performed a voxel-based morphometry study to explore the relationships between semantic and shape categorization tasks and brain morphometric differences in 50 controls. We found significant correlation between categorization performance and the volume of the gray matter in the right anterior middle and inferior temporal gyri. Semantic categorization tasks were associated with more rostral temporal regions than shape categorization tasks. A significant relationship was also shown between white matter volume in the right temporal lobe and performance in the semantic tasks. Tractography revealed that this white matter region involved several projection and association fibers, including the arcuate fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and inferior longitudinal fasciculus. These results suggest that categorization abilities are supported by the anterior portion of the right temporal lobe and its interaction with other areas.

Phytoplankton plasticity drives large variability in carbon fixation efficiency

NASA Astrophysics Data System (ADS)

Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier

2014-12-01

Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

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

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

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

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

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

A Production Function Approach to Regional Environmental-Economic Assessments

EPA Science Inventory

Numerous difficulties await those creating regional-scale environmental assessments, from data having inconsistent spatial or temporal scales to poorly understood environmental processes and indicators. Including socioeconomic variables further complicates the situation. In place...

Anatomical Study of Temporal Fat Compartments and its Clinical Application for Temporal Fat Grafting

PubMed Central

Huang, Ru-Lin; Xie, Yun; Wang, Wenjin; Herrler, Tanja; Zhou, Jia; Zhao, Peijuan; Pu, Lee LQ; Li, Qingfeng

2017-01-01

Abstract Background Low satisfaction rates and severe complications are two major limitations for temporal hollowing augmentation using autologous fat grafting. Despite fat compartments in temporal region have been reported, its clinical applied anatomy for fat grafting have not been the subject of studies that show its benefits objectively and statistically. Objectives To investigate temporal fat compartments and relative neurovascular structures in cadavers, developing a safe and effective fat grafting technique for temporal hollowing augmentation. Methods The study was conducted on 8 cadavers (16 temples). The tissue layers, fat compartments, ligaments, and neurovascular structures in the temporal region were analysed. The variables were the number and location of sentinel veins, perforator vessels of the middle temporal vein. Measurements were taken with a digital calliper. Results Two separate fat compartments, the lateral temporal-cheek fat compartment and lateral orbital fat compartment, were found in the subcutaneous layer, and two separate septum compartments, the upper and lower temporal compartment, were found in the loose areolar tissue layer. One sentinel vein and 1 to 6 perforator vessels were found to travel through the subcutaneous tissue layer, traverse the overlapping tissue layers in the lower temporal septum region, and finally join in the middle temporal vein. Conclusions The four fat compartments in the temporal region are ideal receipt sites for fat grafting. The medial border of the junction of the hairline and temporal line is a safe and effective cannula entry site for temporal fat grafting. The anterior half of the lower temporal compartment is a “zone of caution” for temporal fat grafting. PMID:28520850

Development from childhood to adulthood increases morphological and functional inter-individual variability in the right superior temporal cortex.

PubMed

Bonte, Milene; Frost, Martin A; Rutten, Sanne; Ley, Anke; Formisano, Elia; Goebel, Rainer

2013-12-01

We study the developmental trajectory of morphology and function of the superior temporal cortex (STC) in children (8-9 years), adolescents (14-15 years) and young adults. We analyze cortical surface landmarks and functional MRI (fMRI) responses to voices, other natural categories and tones and examine how hemispheric asymmetry and inter-subject variability change across age. Our results show stable morphological asymmetries across age groups, including a larger left planum temporale and a deeper right superior temporal sulcus. fMRI analyses show that a rightward lateralization for voice-selective responses is present in all groups but decreases with age. Furthermore, STC responses to voices change from being less selective and more spatially diffuse in children to highly selective and focal in adults. Interestingly, the analysis of morphological landmarks reveals that inter-subject variability increases during development in the right--but not in the left--STC. Similarly, inter-subject variability of cortically-realigned functional responses to voices, other categories and tones increases with age in the right STC. Our findings reveal asymmetric developmental changes in brain regions crucial for auditory and voice perception. The age-related increase of inter-subject variability in right STC suggests that anatomy and function of this region are shaped by unique individual developmental experiences. © 2013.

Sensitivity of grassland plant community composition to spatial vs. temporal variation in precipitation

USDA-ARS?s Scientific Manuscript database

Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences...

A Production Function Approach to Regional Environmental Economic Assessments

EPA Science Inventory

Regional-scale environmental assessments require integrating many available types of data having inconsistent spatial or temporal scales. Moreover, the relationships among the environmental variables in the assessment tend to be poorly understood, a situation made even more compl...

Sea level anomaly in the North Atlantic and seas around Europe: Long-term variability and response to North Atlantic teleconnection patterns.

PubMed

Iglesias, Isabel; Lorenzo, M Nieves; Lázaro, Clara; Fernandes, M Joana; Bastos, Luísa

2017-12-31

Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales. Copyright © 2017 Elsevier B.V. All rights reserved.

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

2009-01-01

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Spatio-Temporal Pattern Analysis for Regional Climate Change Using Mathematical Morphology

NASA Astrophysics Data System (ADS)

Das, M.; Ghosh, S. K.

2015-07-01

Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of mathematical morphology. At first, the various climatic zones in the region have been identified by using multifractal cross-correlation analysis (MF-DXA) of different climate variables of interest. Then, the directional granulometry with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to morphological uncertainty index and Hurst exponent. The approach has been evaluated with the daily time series data of land surface temperature (LST) and precipitation rate, collected from Microsoft Research - Fetch Climate Explorer, to analyze the spatio-temporal climatic pattern-change in the Eastern and North-Eastern regions of India throughout four quarters of the 20th century.

Variability, trends, and drivers of regional fluctuations in Australian fire activity

NASA Astrophysics Data System (ADS)

Earl, Nick; Simmonds, Ian

2017-07-01

Throughout the world fire regimes are determined by climate, vegetation, and anthropogenic factors, and they have great spatial and temporal variability. The availability of high-quality satellite data has revolutionized fire monitoring, allowing for a more consistent and comprehensive evaluation of temporal and spatial patterns. Here we utilize a satellite based "active fire" (AF) product to statistically analyze 2001-2015 variability and trends in Australian fire activity and link this to precipitation and large-scale atmospheric structures (namely, the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD)) known to have potential for predicting fire activity in different regions. It is found that Australian fire activity is decreasing (during summer (December-February)) or stable, with high temporal and spatial variability. Eastern New South Wales (NSW) has the strongest decreasing trend (to the 1% confidence level), especially during the winter (JJA) season. Other significantly decreasing areas are Victoria/NSW, Tasmania, and South-east Queensland. These decreasing fire regions are relatively highly populated, so we suggest that the declining trends are due to improved fire management, reducing the size and duration of bush fires. Almost half of all Australian AFs occur during spring (September-November). We show that there is considerable potential throughout Australia for a skillful forecast for future season fire activity based on current and previous precipitation activity, ENSO phase, and to a lesser degree, the IOD phase. This is highly variable, depending on location, e.g., the IOD phase is for more indicative of fire activity in southwest Western Australia than for Queensland.

Spatial and Temporal Variability and Trends in 2001-2016 Global Fire Activity

NASA Astrophysics Data System (ADS)

Earl, Nick; Simmonds, Ian

2018-03-01

Fire regimes across the globe have great spatial and temporal variability, and these are influence by many factors including anthropogenic management, climate, and vegetation types. Here we utilize the satellite-based "active fire" product, from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, to statistically analyze variability and trends in fire activity from the global to regional scales. We split up the regions by economic development, region/geographical land use, clusters of fire-abundant areas, or by religious/cultural influence. Weekly cycle tests are conducted to highlight and quantify part of the anthropogenic influence on fire regime across the world. We find that there is a strong statistically significant decline in 2001-2016 active fires globally linked to an increase in net primary productivity observed in northern Africa, along with global agricultural expansion and intensification, which generally reduces fire activity. There are high levels of variability, however. The large-scale regions exhibit either little change or decreasing in fire activity except for strong increasing trends in India and China, where rapid population increase is occurring, leading to agricultural intensification and increased crop residue burning. Variability in Canada has been linked to a warming global climate leading to a longer growing season and higher fuel loads. Areas with a strong weekly cycle give a good indication of where fire management is being applied most extensively, for example, the United States, where few areas retain a natural fire regime.

The role of visual representations during the lexical access of spoken words

PubMed Central

Lewis, Gwyneth; Poeppel, David

2015-01-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability - concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. PMID:24814579

The role of visual representations during the lexical access of spoken words.

PubMed

Lewis, Gwyneth; Poeppel, David

2014-07-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability--concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. Copyright © 2014 Elsevier Inc. All rights reserved.

Temporal variability of marine debris deposition at Tern Island in the Northwestern Hawaiian Islands.

PubMed

Agustin, Alyssa E; Merrifield, Mark A; Potemra, James T; Morishige, Carey

2015-12-15

A twenty-two year record of marine debris collected on Tern Island is used to characterize the temporal variability of debris deposition at a coral atoll in the Northwestern Hawaiian Islands. Debris deposition tends to be episodic, without a significant relationship to local forcing processes associated with winds, sea level, waves, and proximity to the Subtropical Convergence Zone. The General NOAA Operational Modeling Environment is used to estimate likely debris pathways for Tern Island. The majority of modeled arrivals come from the northeast following prevailing trade winds and surface currents, with trajectories indicating the importance of the convergence zone, or garbage patch, in the North Pacific High region. Although debris deposition does not generally exhibit a significant seasonal cycle, some debris types contain considerable 3 cycle/yr variability that is coherent with wind and surface pressure over a broad region north of Tern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Population Vulnerability to Biannual Cholera Outbreaks and Associated Macro-Scale Drivers in the Bengal Delta

PubMed Central

Akanda, Ali Shafqat; Jutla, Antarpreet S.; Gute, David M.; Sack, R. Bradley; Alam, Munirul; Huq, Anwar; Colwell, Rita R.; Islam, Shafiqul

2013-01-01

The highly populated floodplains of the Bengal Delta have a long history of endemic and epidemic cholera outbreaks, both coastal and inland. Previous studies have not addressed the spatio-temporal dynamics of population vulnerability related to the influence of underlying large-scale processes. We analyzed spatial and temporal variability of cholera incidence across six surveillance sites in the Bengal Delta and their association with regional hydroclimatic and environmental drivers. More specifically, we use salinity and flood inundation modeling across the vulnerable districts of Bangladesh to test earlier proposed hypotheses on the role of these environmental variables. Our results show strong influence of seasonal and interannual variability in estuarine salinity on spring outbreaks and inland flooding on fall outbreaks. A large segment of the population in the Bengal Delta floodplains remain vulnerable to these biannual cholera transmission mechanisms that provide ecologic and environmental conditions for outbreaks over large geographic regions. PMID:24019441

Spatio-temporal dynamics of species richness in coastal fish communities

USGS Publications Warehouse

Lekve, K.; Boulinier, T.; Stenseth, N.C.; Gjøsaeter, J.; Fromentin, J-M.; Hines, J.E.; Nichols, J.D.

2002-01-01

Determining patterns of change in species richness and the processes underlying the dynamics of biodiversity are of key interest within the field of ecology, but few studies have investigated the dynamics of vertebrate communities at a decadal temporal scale. Here, we report findings on the spado-temporal variability in the richness and composition of fish communities along the Norwegian Skagerrak coast having been surveyed for more than half a century. Using statistical models incorporating non-detection and associated sampling variance, we estimate local species richness and changes in species composition allowing us to compute temporal variability in species richness. We tested whether temporal variation could be related to distance to the open sea and to local levels of pollution. Clear differences in mean species richness and temporal variability are observed between fjords that were and were not exposed to the effects of pollution. Altogether this indicates that the fjord is an appropriate scale for studying changes in coastal fish communities in space and time. The year-to-year rates of local extinction and turnover were found to be smaller than spatial differences in community composition. At the regional level, exposure to the open sea plays a homogenizing role, possibly due to coastal currents and advection.

The timing of associative memory formation: frontal lobe and anterior medial temporal lobe activity at associative binding predicts memory

PubMed Central

Hales, J. B.

2011-01-01

The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions. However, most prior memory studies, using concurrently presented stimuli, have failed to examine the temporal aspect of successful associative memory formation to identify when activity in these brain regions is predictive of associative memory formation. In the current study, functional MRI data were acquired while subjects were shown pairs of sequentially presented visual images with a fixed interitem delay within pairs. This design allowed the entire time course of the trial to be analyzed, starting from onset of the first item, across the 5.5-s delay period, and through offset of the second item. Subjects then completed a postscan recognition test for the items and associations they encoded during the scan and their confidence for each. After controlling for item-memory strength, we isolated brain regions selectively involved in associative encoding. Consistent with prior findings, increased regional activity predicting subsequent associative memory success was found in anterior medial temporal lobe regions of left perirhinal and entorhinal cortices and in left prefrontal cortex and lateral occipital regions. The temporal separation within each pair, however, allowed extension of these findings by isolating the timing of regional involvement, showing that increased response in these regions occurs during binding but not during maintenance. PMID:21248058

Analysis of the spatial and temporal variability of mountain snowpack and terrestrial water storage in the Upper Snake River, USA

EPA Science Inventory

The spatial and temporal relationships of winter snowpack and terrestrial water storage (TWS) in the Upper Snake River were analyzed for water years 2001–2010 at a monthly time step. We coupled a regionally validated snow model with gravimetric measurements of the Earth’s water...

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

NASA Astrophysics Data System (ADS)

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

2018-05-01

Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989-2016) suggested the highest probabilities of intermittence (> 35 %) in 1989-1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the temporal variability of intermittent rivers and ephemeral streams.

Functional neuroimaging and presenting psychiatric features in frontotemporal dementia

PubMed Central

Mendez, M F; McMurtray, A; Chen, A K; Shapira, J S; Mishkin, F; Miller, B L

2006-01-01

Background Frontotemporal dementia (FTD) is a behavioural syndrome caused by degeneration of the frontal and anterior temporal lobes. Behavioural disturbances include psychiatric features. Whether patients with FTD present with psychiatric features varies with the initial neuroanatomical variability of FTD. Objective To identify presenting psychiatric changes not part of diagnostic criteria of FTD and contrast them with the degree of hemispheric asymmetry and frontal and temporal hypoperfusion on single photon emission computed tomography (SPECT) imaging. Methods 74 patients who met consensus criteria for FTD were evaluated at a two year follow up. All had brain SPECT on initial presentation. Results of an FTD psychiatric checklist were contrasted with ratings of regional hypoperfusion. Results The regions of predominant hypoperfusion did not correlate with differences on FTD demographic variables but were associated with presenting psychiatric features. Dysthymia and anxiety were associated with right temporal hypoperfusion. “Moria” or frivolous behaviour also occurred with temporal lobe changes, especially on the right. The only significant frontal lobe feature was the presence of a peculiar physical bearing in association with right frontal hypoperfusion. Conclusions Patients with FTD may present with psychiatric changes distinct from the behavioural diagnostic criteria for this disorder. Early temporal involvement is associated with frivolous behaviour and right temporal involvement is associated with emotional disturbances. In contrast, those with right frontal disease may present with alterations in non‐verbal behaviour. PMID:16043457

Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird–prey relationships.

PubMed

Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J

Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the implementation of protective measures could maintain functions and productivity of central place foraging predators.

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

USGS Publications Warehouse

Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

2014-01-01

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Space Technology 5 Multi-Point Observations of Temporal Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2008-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of approximately 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approximately 1 min for meso-scale currents and approximately 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 (ST-5) Observations of Field-Aligned Currents: Temporal Variability

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from STS. The data demonstrate that masoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about I min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 (ST-5) Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that mesoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about 1 min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Spatial patterning of fuels and fire hazard across a central U.S. deciduous forest region

Treesearch

Michael C. Stambaugh; Daniel C. Dey; Richard P. Guyette; Hong S. He; Joseph M. Marschall

2011-01-01

Information describing spatial and temporal variability of forest fuel conditions is essential to assessing overall fire hazard and risk. Limited information exists describing spatial characteristics of fuels in the eastern deciduous forest region, particularly in dry oak-dominated regions that historically burned relatively frequently. From an extensive fuels survey...

Temporal and spatial variability of dissolved organic and inorganic phosphorus, and metrics of phosphorus bioavailability in an upwelling-dominated coastal system

NASA Astrophysics Data System (ADS)

Ruttenberg, Kathleen C.; Dyhrman, Sonya T.

2005-10-01

High-frequency temporal and spatial shifts in the various dissolved P pools (total, inorganic, and organic) are linked to upwelling/relaxation events and to phytoplankton bloom dynamics in the upwelling-dominated Oregon coastal system. The presence and regulation of alkaline phosphatase activity (APA) is apparent in the bulk phytoplankton population and in studies of cell-specific APA using Enzyme Labeled Fluorescence (ELF®). Spatial and temporal variability are also evident in phytoplankton community composition and in APA. The spatial pattern of dissolved phosphorus and APA variability can be explained by bottom-controlled patterns of upwelling, and flushing times of different regions within the study area. The presence of APA in eukaryotic taxa indicates that dissolved organic phosphorus (DOP) may contribute to phytoplankton P nutrition in this system, highlighting the need for a more complete understanding of P cycling and bioavailability in the coastal ocean.

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 (

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention.

PubMed

Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L

2013-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. We have hypothesized that the changes in neural activity observed during increased cholinergic function reflect an increase in neural efficiency that leads to improved task performance. The current study tested this hypothesis by assessing neural efficiency based on cholinergically-mediated effects on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover fMRI study. Following an infusion of physostigmine (1 mg/h) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Physostigmine administration also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus processing regions support the hypothesis that cholinergic augmentation results in enhanced neural efficiency. This article is part of a Special Issue entitled 'Cognitive Enhancers'. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention

PubMed Central

Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L.

2012-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. Previous findings by our group strongly suggested that the changes in neural activity observed during increased cholinergic function may reflect an increase in neural efficiency that leads to improved task performance. The current study was designed to assess the effects of cholinergic enhancement on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover functional magnetic resonance imaging (fMRI) study. Following an infusion of physostigmine (1mg/hr) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions was reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Cholinergic enhancement also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus processing regions provide further support to the hypothesis that cholinergic augmentation results in enhanced neural efficiency. PMID:22906685

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Treesearch

Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell

2010-01-01

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...

Spatio-temporal variability of aerosols in the tropics relationship with atmospheric and oceanic environments

NASA Astrophysics Data System (ADS)

Zuluaga-Arias, Manuel D.

2011-12-01

Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatio-temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses of surface temperature, atmospheric wind, geopotential height, outgoing longwave radiation, water vapor and precipitation together with the climatology of aerosols provide insight on how the variables interact. Different modes of variability, especially in intraseasonal time scales appear as strong modulators of the aerosol distribution. In particular, we investigate how two modes of variability related to the westward propagating synoptic African Easterly Waves of the Tropical Atlantic Ocean affect the horizontal and vertical structure of the environment. The statistical significance of these two modes is tested with the use of two different spectral techniques. The pattern of propagation of aerosol load shows good correspondence with the progression of the atmospheric and oceanic conditions suitable for dust mobilization over the Atlantic Ocean. We present extensions to previous studies related with dust variability over the Atlantic region by evaluating the performance of the long period satellite aerosol retrievals in determining modes of aerosol variability. Results of the covariability between aerosols-environment motivate the use of statistical regression models to test the significance of the forecasting skill of daily AOD time series. The regression models are calibrated using atmospheric variables as predictors from the reanalysis variables. The results show poor forecasting skill with significant error growing after the 3 rd day of the prediction. It is hypothesized that the simplicity of linear models results in an inability to provide a useful forecast.

Neural correlates of word production stages delineated by parametric modulation of psycholinguistic variables.

PubMed

Wilson, Stephen M; Isenberg, Anna Lisette; Hickok, Gregory

2009-11-01

Word production is a complex multistage process linking conceptual representations, lexical entries, phonological forms and articulation. Previous studies have revealed a network of predominantly left-lateralized brain regions supporting this process, but many details regarding the precise functions of different nodes in this network remain unclear. To better delineate the functions of regions involved in word production, we used event-related functional magnetic resonance imaging (fMRI) to identify brain areas where blood oxygen level-dependent (BOLD) responses to overt picture naming were modulated by three psycholinguistic variables: concept familiarity, word frequency, and word length, and one behavioral variable: reaction time. Each of these variables has been suggested by prior studies to be associated with different aspects of word production. Processing of less familiar concepts was associated with greater BOLD responses in bilateral occipitotemporal regions, reflecting visual processing and conceptual preparation. Lower frequency words produced greater BOLD signal in left inferior temporal cortex and the left temporoparietal junction, suggesting involvement of these regions in lexical selection and retrieval and encoding of phonological codes. Word length was positively correlated with signal intensity in Heschl's gyrus bilaterally, extending into the mid-superior temporal gyrus (STG) and sulcus (STS) in the left hemisphere. The left mid-STS site was also modulated by reaction time, suggesting a role in the storage of lexical phonological codes.

NET ANTHROPOGENIC PHOSPHORUS INPUTS; SPATIAL AND TEMPORAL VARIABILITY IN THE CHESAPEAKE BAY REGION

EPA Science Inventory

Coastal watershed eutrophication has increasingly become a regional and global issue as larger proportions of the earth’s human population settle in coastal areas. Human activities on the land have severely impacted the water resources of the Chesapeake Bay, one of the world’s l...

Regional and hemispheric influences on temporal variability in baseline carbon monoxide and ozone over the Northeast US

EPA Science Inventory

Interannual variability in baseline carbon monoxide (CO) and ozone (O3), defined as mixing ratios under minimal influence of recent and local emissions, was studied for seven rural sites in the Northeast US over 2001–2010. Annual baseline CO exhibited statistically signific...

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

Subperiosteal lateral browlift and its relationship to upper blepharoplasty.

PubMed

Gasperoni, C; Salgarello, M; Gargani, G

1993-01-01

Skin redundancy of the upper eyelid is often associated with a variable degree of ptosis of the lateral third of the eyebrow, which increases the extent of the defect. Correcting this condition implies a combination of a temporal lift with a standard upper blepharoplasty. In the temporal lift it is possible to perform an easy subaponeurotic and subperiosteal dissection of the soft tissues of the temporal area through an incision behind the hairline with pleasing and long-lasting results. The brow ptosis is corrected without noticeable scars and with inconspicuous damage to scalp follicles of the temporal region.

Complexities in Subsetting Level 2 Data

NASA Technical Reports Server (NTRS)

Huwe, Paul; Wei, Jennifer; Meyer, David; Silberstein, David S.; Alfred, Jerome; Savtchenko, Andrey K.; Johnson, James E.; Albayrak, Arif; Hearty, Thomas

2017-01-01

Satellite Level 2 data presents unique challenges for tools and services. From nonlinear spatial geometry to inhomogeneous file data structure to inconsistent temporal variables to complex data variable dimensionality to multiple file formats, there are many difficulties in creating general tools for Level 2 data support. At NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are implementing a general Level 2 Subsetting service for Level 2 data to a user-specified spatio-temporal region of interest (ROI). In this presentation, we will unravel some of the challenges faced in creating this service and the strategies we used to surmount them.

The tropospheric biennial oscillation defined by a biennial mode of sea surface temperature and its impact on the atmospheric circulation and precipitation in the tropical eastern Indo-western Pacific region

NASA Astrophysics Data System (ADS)

Kim, Jinju; Kim, Kwang-Yul

2016-10-01

Temporal and spatial patterns of anomalous atmospheric circulation and precipitation over the Indo-Pacific region are analyzed in conjunction with the Tropospheric Biennial Oscillation as represented by the biennial mode of sea surface temperature anomalies (SSTA). The biennial components of key variables are identified independently of other variability via CSEOF analysis. Then, its impact on the Asian-Australian monsoon is examined. The biennial mode exhibits a seasonally distinctive atmospheric response over the tropical eastern Indo-western Pacific (EIWP) region (90°-150°E, 20°S-20°N). In boreal summer, local meridional circulation is a distinguishing characteristic over the tropical EIWP region, whereas a meridionally expanded branch of intensified zonal circulation develops in austral summer. Temporally varying evolution and distinct timing of SSTA phase transition in the Indian and Pacific Oceans is considered a main factor for this variation of circulation in the tropical EIWP region. The impact of the biennial mode is not the same between the two seasons, with different impacts over ocean areas in Asian monsoon and Australian monsoon regions.

Identifying Factors Causing Variability in Greenhouse Gas (GHG) Fluxes in a Polygonal Tundra Landscape

NASA Astrophysics Data System (ADS)

Arora, B.; Wainwright, H. M.; Vaughn, L. S.; Curtis, J. B.; Torn, M. S.; Dafflon, B.; Hubbard, S. S.

2017-12-01

Greenhouse gas (GHG) flux variations in Arctic tundra environments are important to understand because of the vast amount of soil carbon stored in these regions and the potential of these regions to convert from a global carbon sink to a source under warmer conditions. Multiple factors potentially contribute to GHG flux variations observed in these environments, including snowmelt timing, growing season length, active layer thickness, water table variations, and temperature fluctuations. The objectives of this study are to investigate temporal variability in CO2 and CH4 fluxes at Barrow, AK over three successive growing seasons (2012-14) and to determine the factors influencing this variability using a novel entropy-based classification scheme. We analyzed soil, vegetation, and climate parameters as well as GHG fluxes at multiple locations within low-, flat- and high-centered polygons at Barrow, AK as part of the Next Generation Ecosystem Experiment (NGEE) Arctic project. Entropy results indicate that different environmental factors govern variability in GHG fluxes under different spatiotemporal settings. In particular, flat-centered polygons are more likely to become significant sources of CO2 during warm and dry years as opposed to high-centered polygons that contribute considerably to CO2 emissions during cold and wet years. In contrast, the highest CH4 emissions were always associated with low-centered polygons. Temporal variability in CO2 fluxes was primarily associated with factors affecting soil temperature and/or vegetation dynamics during early and late season periods. Temporal variability in CH4 fluxes was primarily associated with changes in vegetation cover and its covariability with primary controls such as seasonal thaw—rather than direct response to changes in soil moisture. Overall, entropy results document which factors became important under different spatiotemporal settings, thus providing clues concerning the manner in which ecosystem properties may be altered regionally in a future climate.

Applying probabilistic temporal and multisite data quality control methods to a public health mortality registry in Spain: a systematic approach to quality control of repositories.

PubMed

Sáez, Carlos; Zurriaga, Oscar; Pérez-Panadés, Jordi; Melchor, Inma; Robles, Montserrat; García-Gómez, Juan M

2016-11-01

To assess the variability in data distributions among data sources and over time through a case study of a large multisite repository as a systematic approach to data quality (DQ). Novel probabilistic DQ control methods based on information theory and geometry are applied to the Public Health Mortality Registry of the Region of Valencia, Spain, with 512 143 entries from 2000 to 2012, disaggregated into 24 health departments. The methods provide DQ metrics and exploratory visualizations for (1) assessing the variability among multiple sources and (2) monitoring and exploring changes with time. The methods are suited to big data and multitype, multivariate, and multimodal data. The repository was partitioned into 2 probabilistically separated temporal subgroups following a change in the Spanish National Death Certificate in 2009. Punctual temporal anomalies were noticed due to a punctual increment in the missing data, along with outlying and clustered health departments due to differences in populations or in practices. Changes in protocols, differences in populations, biased practices, or other systematic DQ problems affected data variability. Even if semantic and integration aspects are addressed in data sharing infrastructures, probabilistic variability may still be present. Solutions include fixing or excluding data and analyzing different sites or time periods separately. A systematic approach to assessing temporal and multisite variability is proposed. Multisite and temporal variability in data distributions affects DQ, hindering data reuse, and an assessment of such variability should be a part of systematic DQ procedures. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

PubMed Central

Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

2011-01-01

To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

OBSERVING CORONAL NANOFLARES IN ACTIVE REGION MOSS

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

Testa, Paola; DeLuca, Ed; Golub, Leon

2013-06-10

The High-resolution Coronal Imager (Hi-C) has provided Fe XII 193A images of the upper transition region moss at an unprecedented spatial ({approx}0.''3-0.''4) and temporal (5.5 s) resolution. The Hi-C observations show in some moss regions variability on timescales down to {approx}15 s, significantly shorter than the minute-scale variability typically found in previous observations of moss, therefore challenging the conclusion of moss being heated in a mostly steady manner. These rapid variability moss regions are located at the footpoints of bright hot coronal loops observed by the Solar Dynamics Observatory/Atmospheric Imaging Assembly in the 94 A channel, and by the Hinode/X-Raymore » Telescope. The configuration of these loops is highly dynamic, and suggestive of slipping reconnection. We interpret these events as signatures of heating events associated with reconnection occurring in the overlying hot coronal loops, i.e., coronal nanoflares. We estimate the order of magnitude of the energy in these events to be of at least a few 10{sup 23} erg, also supporting the nanoflare scenario. These Hi-C observations suggest that future observations at comparable high spatial and temporal resolution, with more extensive temperature coverage, are required to determine the exact characteristics of the heating mechanism(s).« less

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

NASA Technical Reports Server (NTRS)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Constancy despite variability: Local and regional macrofaunal diversity in intertidal seagrass beds

NASA Astrophysics Data System (ADS)

Boyé, Aurélien; Legendre, Pierre; Grall, Jacques; Gauthier, Olivier

2017-12-01

The importance of seagrass habitat for the diversity of benthic fauna has been extensively studied worldwide. Most of the information available is, however, about α diversity while little consideration has been given to β diversity. To fill the knowledge gaps regarding the variability of epifaunal and infaunal seagrass assemblages at large spatial and temporal scales, we scrutinized an extensive dataset covering five years of monitoring of eight intertidal Zostera marina meadows around Brittany (France). High species richness arose at the regional scale from the combination of high local diversity of the meadows and substantial among-meadows β diversity. Epifauna and infauna appeared as distinct self-communities as they displayed different spatial and temporal patterns and varied in their responses to local hydrological conditions. Infauna had higher total β diversity than epifauna due to a tighter link to the great variability of local environmental conditions in the region. Both exhibited substantial variations in species composition and community structure with variations of dominant species that were accompanied by extensive change in numerous rare species. The dominant epifaunal species were all grazers. Changes in species composition were induced mostly by species replacement and rarely by richness differences between meadows. Indeed, species richness remained within a narrow range for all seagrass beds, suggesting a potential carrying capacity for species richness of the meadows. Overall, all meadows contributed equally to the regional turnover of seagrass macrofauna, emphasizing high variability and complementarity among beds at the regional scale. The implications of this substantial within-seagrass variability for the functioning of benthic ecosystems at broad scale and for conservation purposes in habitat mosaics warrant further investigations but our results clearly advocate taking into account within-habitat variation when evaluating the diversity of benthic habitats and the potential effect of habitat loss.

Global trends in visibility: Implications for dust sources

USGS Publications Warehouse

Mahowald, N.M.; Ballantine, J.A.; Feddema, J.; Ramankutty, N.

2007-01-01

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 359 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility derived variables and AERONET optical depths indicate a moderate correlation (???0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with visibility, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974-2003.

Calibration and validation of CSM-CROPGRO-cotton model using lysimeter data in the Texas High Plains

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) is one of the most important food and fiber producing regions in the Ogallala Aquifer Region, currently facing rapid decline of groundwater levels. Predicated climate extremes and high temporal variability in growing season precipitation in the future may demand growers t...

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

PubMed

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Long-term demography of the Northern Goshawk in a variable environment

Treesearch

Richard T. Reynolds; Jeffrey S. Lambert; Curtis H. Flather; Gary C. White; Benjamin J. Bird; L. Scott Baggett; Carrie Lambert; Shelley Bayard De Bolo

2017-01-01

The Nearctic northern goshawk (Accipiter gentilis atricapillis) is a resident of conifer, broadleaf, and mixed forests from the boreal to the southwestern montane regions of North America. We report on a 20-year mark-recapture investigation (1991-2010) of the distribution and density of breeders, temporal and spatial variability in breeding, nestling sex ratios, local...

Spatio-temporal Variability of Stratified Snowpack Cold Content Observed in the Rocky Mountains

NASA Astrophysics Data System (ADS)

Schmidt, J. S.; Sexstone, G. A.; Serreze, M. C.

2017-12-01

Snowpack cold content (CCsnow) is the energy required to bring a snowpack to an isothermal temperature of 0.0°C. The spatio-temporal variability of CCsnow is complex as it is a measure that integrates the response of a snowpack to each component of the snow-cover energy balance. Snow and ice at high elevation is climate sensitive water storage for the Western U.S. Therefore, an improved understanding of the spatio-temporal variability of CCsnow may provide insight into snowpack dynamics and sensitivity to climate change. In this study, stratified snowpit observations of snow water equivalent (SWE) and snow temperature (Tsnow) from the USGS Rocky Mountain Snowpack network (USGS RMS) were used to evaluate vertical CCsnow profiles over a 16-year period in Montana, Idaho, Wyoming, Colorado and New Mexico. Since 1993, USGS RMS has collected snow chemistry, snow temperature, and SWE data throughout the Rocky Mountain region, making it well positioned for Anthropocene cryosphere benchmarking and climate change interpretation. Spatial grouping of locations based on similar CCsnow characteristics was evaluated and trend analyses were performed. Additionally, we evaluated the regional relation of CCsnow to snowmelt timing. CCsnow was more precisely calculated and more representative using vertically stratified field observed values than bulk values, which highlights the utility of the snowpack dataset presented here. Location specific annual and 16 year mean stratified snowpit profiles of SWE, Tsnow, and CCsnow well represent the physical geography and past weather patterns acting on the snowpack. Observed trends and spatial variability of CCsnow profiles explored by this study provides an improved understanding of changing snowpack behavior in the western U.S., and will be useful for assessing the regional sensitivity of snowpacks to future climate change.

Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Wanchang

2017-10-01

The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation, evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to develop effective eco-environment management plans and strategies that address the consequences of climate changes.

Methane Seeps in the Gulf of Mexico: repeat acoustic surveying shows highly temporally and spatially variable venting

NASA Astrophysics Data System (ADS)

Beaumont, B. C.; Raineault, N.

2016-02-01

Scientists have recognized that natural seeps account for a large amount of methane emissions. Despite their widespread occurrence in areas like the Gulf of Mexico, little is known about the temporal variability and site-scale spatial variability of venting over time. We used repeat acoustic surveys to compare multiple days of seep activity and determine the changes in the locus of methane emission and plume height. The Sleeping Dragon site was surveyed with an EM302 multibeam sonar on three consecutive days in 2014 and 4 days within one week in 2015. The data revealed three distinctive plume regions. The locus of venting varied by 10-60 meters at each site. The plume that exhibited the least spatial variability in venting, was also the most temporally variable. This seep was present in one-third of survey dates in 2014 and three quarters of survey dates in 2015, showing high day-to-day variability. The plume height was very consistent for this plume, whereas the other plumes were more consistent temporally, but varied in maximum plume height detection by 25-85 m. The single locus of emission at the site that had high day-to-day variability may be due to a single conduit for methane release, which is sometimes closed off by carbonate or clathrate hydrate formation. In addition to day-to-day temporal variability, the locus of emission at one site was observed to shift from a point-source in 2014 to a diffuse source in 2015 at a nearby location. ROV observations showed that one of the seep sites that closed off temporarily, experienced an explosive breakthrough of gas, releasing confined methane and blowing out rock. The mechanism that causes on/off behavior of certain plumes, combined with the spatial variability of the locus of methane release shown in this study may point to carbonate or hydrate formation in the seep plumbing system and should be further investigated.

Spatio-Temporal Variability in Accretion and Erosion of Coastal Foredunes in the Netherlands: Regional Climate and Local Topography

PubMed Central

Keijsers, Joep G. S.; Poortinga, Ate; Riksen, Michel J. P. M.; Maroulis, Jerry

2014-01-01

Depending on the amount of aeolian sediment input and dune erosion, dune size and morphology change over time. Since coastal foredunes play an important role in the Dutch coastal defence, it is important to have good insight in the main factors that control these changes. In this paper the temporal variations in foredune erosion and accretion were studied in relation to proxies for aeolian transport potential and storminess using yearly elevation measurements from 1965 to 2012 for six sections of the Dutch coast. Longshore differences in the relative impacts of erosion and accretion were examined in relation to local beach width. The results show that temporal variability in foredune accretion and erosion is highest in narrow beach sections. Here, dune erosion alternates with accretion, with variability displaying strong correlations with yearly values of storminess (maximum sea levels). In wider beach sections, dune erosion is less frequent, with lower temporal variability and stronger correlations with time series of transport potential. In erosion dominated years, eroded volumes decrease from narrow to wider beaches. When accretion dominates, dune-volume changes are relatively constant alongshore. Dune erosion is therefore suggested to control spatial variability in dune-volume changes. On a scale of decades, the volume of foredunes tends to increase more on wider beaches. However, where widths exceed 200 to 300 m, this trend is no longer observed. PMID:24603812

Spatio-temporal variability in accretion and erosion of coastal foredunes in the Netherlands: regional climate and local topography.

PubMed

Keijsers, Joep G S; Poortinga, Ate; Riksen, Michel J P M; Maroulis, Jerry

2014-01-01

Depending on the amount of aeolian sediment input and dune erosion, dune size and morphology change over time. Since coastal foredunes play an important role in the Dutch coastal defence, it is important to have good insight in the main factors that control these changes. In this paper the temporal variations in foredune erosion and accretion were studied in relation to proxies for aeolian transport potential and storminess using yearly elevation measurements from 1965 to 2012 for six sections of the Dutch coast. Longshore differences in the relative impacts of erosion and accretion were examined in relation to local beach width. The results show that temporal variability in foredune accretion and erosion is highest in narrow beach sections. Here, dune erosion alternates with accretion, with variability displaying strong correlations with yearly values of storminess (maximum sea levels). In wider beach sections, dune erosion is less frequent, with lower temporal variability and stronger correlations with time series of transport potential. In erosion dominated years, eroded volumes decrease from narrow to wider beaches. When accretion dominates, dune-volume changes are relatively constant alongshore. Dune erosion is therefore suggested to control spatial variability in dune-volume changes. On a scale of decades, the volume of foredunes tends to increase more on wider beaches. However, where widths exceed 200 to 300 m, this trend is no longer observed.

Life-history strategies associated with local population variability confer regional stability.

PubMed

Pribil, Stanislav; Houlahan, Jeff E

2003-07-07

A widely held ecological tenet is that, at the local scale, populations of K-selected species (i.e. low fecundity, long lifespan and large body size) will be less variable than populations of r-selected species (i.e. high fecundity, short lifespan and small body size). We examined the relationship between long-term population trends and life-history attributes for 185 bird species in the Czech Republic and found that, at regional spatial scales and over moderate temporal scales (100-120 years), K-selected bird species were more likely to show both large increases and decreases in population size than r-selected species. We conclude that life-history attributes commonly associated with variable populations at the local scale, confer stability at the regional scale.

Post-heading heat stress and yield impact in winter wheat of China.

PubMed

Liu, Bing; Liu, Leilei; Tian, Liying; Cao, Weixing; Zhu, Yan; Asseng, Senthold

2014-02-01

Wheat is sensitive to high temperatures, but the spatial and temporal variability of high temperature and its impact on yield are often not known. An analysis of historical climate and yield data was undertaken to characterize the spatial and temporal variability of heat stress between heading and maturity and its impact on wheat grain yield in China. Several heat stress indices were developed to quantify heat intensity, frequency, and duration between heading and maturity based on measured maximum temperature records of the last 50 years from 166 stations in the main wheat-growing region of China. Surprisingly, heat stress between heading and maturity was more severe in the generally cooler northern wheat-growing regions than the generally warmer southern regions of China, because of the delayed time of heading with low temperatures during the earlier growing season and the exposure of the post-heading phase into the warmer part of the year. Heat stress between heading and maturity has increased in the last decades in most of the main winter wheat production areas of China, but the rate was higher in the south than in the north. The correlation between measured grain yields and post-heading heat stress and average temperature were statistically significant in the entire wheat-producing region, and explained about 29% of the observed spatial and temporal yield variability. A heat stress index considering the duration and intensity of heat between heading and maturity was required to describe the correlation of heat stress and yield variability. Because heat stress is a major cause of yield loss and the number of heat events is projected to increase in the future, quantifying the future impact of heat stress on wheat production and developing appropriate adaptation and mitigation strategies are critical for developing food security policies in China and elsewhere. © 2013 John Wiley & Sons Ltd.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Ultrafast 2-dimensional image monitoring and array-based passive cavitation detection for ultrasound contrast agent destruction in a variably sized region.

PubMed

Xu, Shanshan; Hu, Hong; Jiang, Hujie; Xu, Zhi'an; Wan, Mingxi

2014-11-01

A combined approach was proposed, based on programmable ultrasound equipment, to simultaneously monitor surviving microbubbles and detect cavitation activity during microbubble destruction in a variably sized region for use in ultrasound contrast agent (UCA)-enhanced therapeutic ultrasound applications. A variably sized focal region wherein the acoustic pressure was above the UCA fragmentation threshold was synthesized at frequencies of 3, 4, 5, and 6 MHz with a linear broadband imaging probe. The UCAs' temporal and spatial distribution during the microbubbles' destruction was monitored in a 2-dimensional imaging plane at 5 MHz and a frame rate of 400 Hz, and simultaneously, broadband noise emissions during the microbubbles' fragmentation were extracted by using the backscattered signals produced by the focused release bursts (ie, destruction pulses) themselves. Afterward, the temporal evolution of broadband noise emission, the surviving microbubbles in a region of interest (ROI), and the destruction area in a static UCA suspension were computed. Then the inertial cavitation dose, destruction rate of microbubbles in the ROI, and area of the destruction region were determined. It was found that an increasing pulse length and a decreasing transmit aperture and excitation frequency were correlated with an increased inertial cavitation dose, microbubble destruction rate, and destruction area. Furthermore, it was obvious that the microbubble destruction rate was significantly correlated with the inertial cavitation dose (P < .05). In addition, the intensity decrease in the ROI was significantly correlated with the destruction area (P < .05). By the proposed strategy, microbubbles could be destroyed in a variably sized region, and destruction efficiency as well as the corresponding inertial cavitation dose could be regulated by manipulating the transmission parameters. © 2014 by the American Institute of Ultrasound in Medicine.

A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products

NASA Technical Reports Server (NTRS)

Chou, Shu-Hsien; Nelkin, Eric; Ardizzone, Joe; Atlas, Robert M.

2003-01-01

To improve our understanding of global energy and water cycle variability, and to improve model simulations of climate variations, it is vital to have accurate latent heat fluxes (LHF) over global oceans. Monthly LHF, 10-m wind speed (U10m), 10-m specific humidity (Q10h), and sea-air humidity difference (Qs-Q10m) of GSSTF2 (version 2 Goddard Satellite-based Surface Turbulent Fluxes) over global Oceans during 1992-93 are compared with those of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data), NCEP (NCEP/NCAR reanalysis). The mean differences, standard deviations of differences, and temporal correlation of these monthly variables over global Oceans during 1992-93 between GSSTF2 and each of the three datasets are analyzed. The large-scale patterns of the 2yr-mean fields for these variables are similar among these four datasets, but significant quantitative differences are found. The temporal correlation is higher in the northern extratropics than in the south for all variables, with the contrast being especially large for da Silva as a result of more missing ship data in the south. The da Silva has extremely low temporal correlation and large differences with GSSTF2 for all variables in the southern extratropics, indicating that da Silva hardly produces a realistic variability in these variables. The NCEP has extremely low temporal correlation (0.27) and large spatial variations of differences with GSSTF2 for Qs-Q10m in the tropics, which causes the low correlation for LHF. Over the tropics, the HOAPS LHF is significantly smaller than GSSTF2 by approx. 31% (37 W/sq m), whereas the other two datasets are comparable to GSSTF2. This is because the HOAPS has systematically smaller LHF than GSSTF2 in space, while the other two datasets have very large spatial variations of large positive and negative LHF differences with GSSTF2 to cancel and to produce smaller regional-mean differences. Our analyses suggest that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other three flux datasets examined, although those of GSSTF2 are still subject to regional biases.

Editorial for Journal of Hydrology: Regional Studies

USGS Publications Warehouse

Willems, Patrick; Batelaan, Okke; Hughes, Denis A.; Swarzenski, Peter W.

2014-01-01

Hydrological regimes and processes show strong regional differences. While some regions are affected by extreme drought and desertification, others are under threat of increased fluvial and/or pluvial floods. Changes to hydrological systems as a consequence of natural variations and human activities are region-specific. Many of these changes have significant interactions with and implications for human life and ecosystems. Amongst others, population growth, improvements in living standards and other demographic and socio-economic trends, related changes in water and energy demands, change in land use, water abstractions and returns to the hydrological system (UNEP, 2008), introduce temporal and spatial changes to the system and cause contamination of surface and ground waters. Hydro-meteorological boundary conditions are also undergoing spatial and temporal changes. Climate change has been shown to increase temporal and spatial variations of rainfall, increase temperature and cause changes to evapotranspiration and other hydro-meteorological variables (IPCC, 2013). However, these changes are also region specific. In addition to these climate trends, (multi)-decadal oscillatory changes in climatic conditions and large variations in meteorological conditions will continue to occur.

Global trends in visibility: Implications for dust sources

USGS Publications Warehouse

Mahowald, N.M.; Ballantine, J.A.; Feddema, J.; Ramankutty, N.

2007-01-01

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. We did this by looking at time series of visibility derived variables and their correlations with precipitation, drought, winds, land use and grazing. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 357 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility-derived variables and AERONET optical depths indicate a moderate correlation (0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility-derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the Palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility-derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with VIS5 or EXT, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974-2003.

Assessing site-specific spatio-temporal variations in hydrogen and oxygen stable isotopes of human drinking water

NASA Astrophysics Data System (ADS)

Kennedy, C. D.; Bowen, G. J.; Ehleringer, J. R.

2008-12-01

Stable isotope ratios of hydrogen and oxygen (δ2H and δ18O) are environmental forensic tracers that can be used to constrain the origin and movement of animals, people, and products. The fundamental assumption underlying this method is that water resources at different geographic locations have distinct and characteristic isotopic signatures that are assimilated into organic tissues. Although much is known about regional-scale spatio-temporal variability in δ2H and δ18O of water, few studies have addressed the question of how distinct these geographic and seasonal patterns are for any given site. To address this question, a 2-year survey of δ2H and δ18O in tap water from across the contiguous U.S. and Canada was conducted. The data show that seasonal variability in δ2H and δ18O of tap water is generally low (<10 ‰ for δ2H), and those with the highest variability can be classified as: a) cities or towns in areas of high climate seasonality, or b) large cities in arid or seasonally arid regions which access and switch among multiple water sources throughout the year. The data suggest that inter-annual variation in tap water isotope ratios is typically low, with a median difference for month-month pairs during the 2 sampling years of 2.7 (δ2H). The results from this study confirm the existence of temporal variability in δ2H and δ18O of tap water, but suggest that this variability in human-managed systems is highly damped and may be amenable to classification, modeling, and prediction. In all, the data provide the foundation for incorporating temporal variation in predictive models of water and organic δ2H and δ18O, leading to more robust and statistically defensible tests of geographic origin.

Spatial and Temporal Means and Variability of Arctic Sea Ice Climate Indicators from Satellite Data

NASA Astrophysics Data System (ADS)

Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S.

2017-12-01

Arctic sea ice has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer ice coverage. For the Arctic as a whole, the long-term trend for the annual sea ice extent (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the trends of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea ice climate indicators, such as the annual SIE minimum and maximum, snow/ice melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation.

Estimation of the fractional coverage of rainfall in climate models

NASA Technical Reports Server (NTRS)

Eltahir, E. A. B.; Bras, R. L.

1993-01-01

The fraction of the grid cell area covered by rainfall, mu, is an essential parameter in descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, based on extensive observations of storm areas and rainfall volumes. Storm area and rainfall volume are often linearly related; this relation can be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing mu, which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, and the spatial and temporal resolution of the model. The new formula is applied in computing mu over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed.

Spatial and temporal distribution of ambient nitric acid and ammonia in the Athabasca Oil Sands Region, Alberta

Treesearch

A. Bytnerowicz; W. Fraczek; S. Schilling; D. Alexander

2010-01-01

Monthly average ambient concentrations of gaseous nitric acid (HNO3) and ammonia (NH3) were monitored at the Athabasca Oils Sands Region (AOSR), Alberta, Canada, between May 2005 and September 2008. Generally, concentrations of both pollutants were elevated and highly variable in space and time. The highest atmospheric...

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic rainfall time series model was developed that incorporates the entire range of multiscale variabilities observed in each region, including within-storm, intra-annual, interannual, and interdecadal variability. Such ability to characterize, model, and synthetically generate realistic time series of rainfall intensities is essential for addressing many hydrological problems, including estimation of flood and drought frequencies, pesticide risk assessment, and landslide frequencies.

Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds

NASA Astrophysics Data System (ADS)

Morison, Matthew Q.; Macrae, Merrin L.; Petrone, Richard M.; Fishback, LeeAnn

2017-12-01

Across the circumpolar north, the fate of small freshwater ponds and lakes (< 1 km2) has been the subject of scientific interest due to their ubiquity in the landscape, capacity to exchange carbon and energy with the atmosphere, and their potential to inform researchers about past climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely mediated by processes within ponds. This work demonstrates the importance of understanding hydrologically driven chemodynamics in permafrost ponds on multiple scales (seasonal and event scale).

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts.

PubMed

Lee, Hyung Joo; Gent, Janneane F; Leaderer, Brian P; Koutrakis, Petros

2011-05-01

To protect public health from PM(2.5) air pollution, it is critical to identify the source types of PM(2.5) mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM(2.5) source types and quantify the source contributions to PM(2.5) in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM(2.5) mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM(2.5). Due to sparse ground-level PM(2.5) monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM(2.5) monitors is more reliable than using data from the nearest central monitor. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey.

PubMed

Sekertekin, Aliihsan; Kutoglu, Senol Hakan; Kaya, Sinasi

2016-01-01

The aim of this study is to analyze spatio-temporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 °C), forestland (3 °C), city and town centers (4.2 °C), municipal rubbish tip (-3.9 °C), coal dump site (12.2 °C), and power plants' region (7 °C) were presented. In addition, the results indicated that the mean LST difference between forestland and city centers was approximately 5 °C, and the difference between forestland and industrial enterprises was almost 8 °C for all years. Spatio-temporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development.

Modelled and observed mass balance of Rikha Samba Glacier, Nepal, Central Himalaya

NASA Astrophysics Data System (ADS)

Gurung, T. R.; Kayastha, R. B.; Fujita, K.; Sinisalo, A. K.; Stumm, D.; Joshi, S.; Litt, M.

2016-12-01

Glacier mass balance variability has an implication for the regional water resources and it helps to understand the response of glacier to climate change in the Himalayan region. Several mass balance studies have been started in the Himalayan region since 1970s, but they are characterized by frequent temporal gaps and a poor spatial representatively. This study aims at bridging the temporal gaps in a long term mass balance series of the Rikha Samba glacier (5383 - 6475 m a.s.l.), a benchmark glacier located in the Hidden Valley, Mustang, Nepal. The ERA Interim reanalysis data for the period 2011-2015 is calibrated with the observed meteorological variables from an AWS installed near the glacier terminus. We apply an energy mass balance model, validated with the available in-situ measurements for the years 1998 and 2011-2015. The results show that the glacier is shrinking at a moderate negative mass balance rate for the period 1995 to 2015 and the high altitude location of Rikha Samba also prevents a bigger mass loss compared to other small Himalayan glaciers. Precipitation from July to January and the mean air temperature from June to October are the most influential climatic parameters of the annual mass balance variability of Rikha Samba glacier.

Spatial and Temporal Variation in the Effects of Climatic Variables on Dugong Calf Production.

PubMed

Fuentes, Mariana M P B; Delean, Steven; Grayson, Jillian; Lavender, Sally; Logan, Murray; Marsh, Helene

2016-01-01

Knowledge of the relationships between environmental forcing and demographic parameters is important for predicting responses from climatic changes and to manage populations effectively. We explore the relationships between the proportion of sea cows (Dugong dugon) classified as calves and four climatic drivers (rainfall anomaly, Southern Oscillation El Niño Index [SOI], NINO 3.4 sea surface temperature index, and number of tropical cyclones) at a range of spatially distinct locations in Queensland, Australia, a region with relatively high dugong density. Dugong and calf data were obtained from standardized aerial surveys conducted along the study region. A range of lagged versions of each of the focal climatic drivers (1 to 4 years) were included in a global model containing the proportion of calves in each population crossed with each of the lagged versions of the climatic drivers to explore relationships. The relative influence of each predictor was estimated via Gibbs variable selection. The relationships between the proportion of dependent calves and the climatic drivers varied spatially and temporally, with climatic drivers influencing calf counts at sub-regional scales. Thus we recommend that the assessment of and management response to indirect climatic threats on dugongs should also occur at sub-regional scales.

Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2015-09-30

spatial and temporal distribution of key marine organisms over multiple trophic levels, and (2) natural and anthropogenic variability in ecosystem...areas of climate modeling in upwelling regions (E. Curchitser), physical-biological modeling in the CCLME (J. Fiechter and C. Edwards), data...optimal growth conditions). By comparing interannual changes in fat depot against EOF modes for environmental variability (i.e., SST) and prey

Temporal variability of neustonic ichthyoplankton assemblages of the eastern Pacific warm pool: Can community structure be linked to climate variability?

NASA Astrophysics Data System (ADS)

Ignacio Vilchis, L.; Ballance, Lisa T.; Watson, William

2009-01-01

Considerable evidence exists, showing an accelerated warming trend on earth during the past 40-50 years, attributed mainly to anthropogenic factors. Much of this excess heat is stored in the world's oceans, likely resulting in increased environmental variability felt by marine ecosystems. The long-term effects of this phenomenon on oceanic tropical ecosystems are largely unknown, and our understanding of its effects could be facilitated by long-term studies of how species compositions change with time. Ichthyoplankton, in particular, can integrate physical, environmental and ecological factors making them excellent model taxa to address this question. While on eight (1987-1990, 1992 and 1998-2000) NOAA Fisheries cruises to the eastern Pacific warm pool, we characterized the thermal and phytoplankton pigment structure of the water column, as well as the neustonic ichthyoplankton community using CTD casts and Manta (surface) net tows. Over the 13-year period, 852 CTD and Manta tow stations were completed. We divided the study area into three regions based on regional oceanography, thermocline depth and productivity, as well as a longitudinal gradient in species composition among stations. We then analyzed temporal trends of ichthyoplankton species composition within each region by pooling stations by region and year and making pairwise comparisons of community similarity between all combinations of the eight cruises within each region. We also identified environment-specific species assemblages and station groupings using hierarchical clustering and non-metric multi-dimensional scaling (MDS). Our analyses revealed a longitudinal gradient in community structure and temporal stability of ichthyoplankton species composition. Over the 13 years ichthyoplankton assemblages in the two westernmost regions varied less than in the eastern region. MDS and cluster analyses identified five ichthyoplankton assemblages that corresponded to oceanographic habitats and a gradient in community composition. We hypothesize that the changes in thermocline depth during the El Niños of 1987-1988, 1997-1998 and the extended period of warmth during 1990-1994 altered productivity sufficiently to cause a shift in the abundances of foundation species of the upwelling systems of the eastern Pacific warm pool. Our study suggests that ichthyoplankton assemblages in oligotrophic waters are more resilient to changes in the thermocline than assemblages in upwelling regions; or that oligotrophic regions simply have less physical variation compared to upwelling regions.

Small-scale variability in peatland pore-water biogeochemistry, Hudson Bay Lowland, Canada.

PubMed

Ulanowski, T A; Branfireun, B A

2013-06-01

The Hudson Bay Lowland (HBL) of northern Ontario, Manitoba and Quebec, Canada is the second largest contiguous peatland complex in the world, currently containing more than half of Canada's soil carbon. Recent concerns about the ecohydrological impacts to these large northern peatlands resulting from climate change and resource extraction have catalyzed a resurgence in scientific research into this ecologically important region. However, the sheer size, heterogeneity and elaborate landscape arrangements of this ecosystem raise important questions concerning representative sampling of environmental media for chemical or physical characterization. To begin to quantify such variability, this study assessed the small-scale spatial (1m) and short temporal (21 day) variability of surface pore-water biogeochemistry (pH, dissolved organic carbon, and major ions) in a Sphagnum spp.-dominated, ombrotrophic raised bog, and a Carex spp.-dominated intermediate fen in the HBL. In general, pore-water pH and concentrations of dissolved solutes were similar to previously reported literature values from this region. However, systematic sampling revealed consistent statistically significant differences in pore-water chemistries between the bog and fen peatland types, and large within-site spatiotemporal variability. We found that microtopography in the bog was associated with consistent differences in most biogeochemical variables. Temporal changes in dissolved solute chemistry, particularly base cations (Na(+), Ca(2+) and Mg(2+)), were statistically significant in the intermediate fen, likely a result of a dynamic connection between surficial waters and mineral-rich deep groundwater. In both the bog and fen, concentrations of SO4(2-) showed considerable spatial variability, and a significant decrease in concentrations over the study period. The observed variability in peatland pore-water biogeochemistry over such small spatial and temporal scales suggests that under-sampling in northern peatland environments could lead to erroneous conclusions concerning the abundance and distribution of natural elements and pollutants alike. Copyright © 2013 Elsevier B.V. All rights reserved.

Site-specific nutrient management systems

USDA-ARS?s Scientific Manuscript database

Site-specific nutrient management systems were created to manage for spatial and temporal variability in biophysical factors that determine the availability and demand of crop nutrients. These systems differ among geographical regions in the information utilized and way they operate to accomplish th...

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

Temporal dynamics of estuarine phytoplankton: A case study of San Francisco Bay

USGS Publications Warehouse

Cloern, J.E.; Cole, B.E.; Wong, R.L.J.; Alpine, A.E.

1985-01-01

Detailed surveys throughout San Francisco Bay over an annual cycle (1980) show that seasonal variations of phytoplankton biomass, community composition, and productivity can differ markedly among estuarine habitat types. For example, in the river-dominated northern reach (Suisun Bay) phytoplankton seasonality is characterized by a prolonged summer bloom of netplanktonic diatoms that results from the accumulation of suspended particulates at the convergence of nontidal currents (i.e. where residence time is long). Here turbidity is persistently high such that phytoplankton growth and productivity are severely limited by light availability, the phytoplankton population turns over slowly, and biological processes appear to be less important mechanisms of temporal change than physical processes associated with freshwater inflow and turbulent mixing. The South Bay, in contrast, is a lagoon-type estuary less directly coupled to the influence of river discharge. Residence time is long (months) in this estuary, turbidity is lower and estimated rates of population growth are high (up to 1-2 doublings d-1), but the rapid production of phytoplankton biomass is presumably balanced by grazing losses to benthic herbivores. Exceptions occur for brief intervals (days to weeks) during spring when the water column stratifies so that algae retained in the surface layer are uncoupled from benthic grazing, and phytoplankton blooms develop. The degree of stratification varies over the neap-spring tidal cycle, so the South Bay represents an estuary where (1) biological processes (growth, grazing) and a physical process (vertical mixing) interact to cause temporal variability of phytoplankton biomass, and (2) temporal variability is highly dynamic because of the short-term variability of tides. Other mechanisms of temporal variability in estuarine phytoplankton include: zooplankton grazing, exchanges of microalgae between the sediment and water column, and horizontal dispersion which transports phytoplankton from regions of high productivity (shallows) to regions of low productivity (deep channels). Multi-year records of phytoplankton biomass show that large deviations from the typical annual cycles observed in 1980 can occur, and that interannual variability is driven by variability of annual precipitation and river discharge. Here, too, the nature of this variability differs among estuary types. Blooms occur only in the northern reach when river discharge falls within a narrow range, and the summer biomass increase was absent during years of extreme drought (1977) or years of exceptionally high discharge (1982). In South Bay, however, there is a direct relationship between phytoplankton biomass and river discharge. As discharge increases so does the buoyancy input required for density stratification, and wet years are characterized by persistent and intense spring blooms. ?? 1985 Dr W. Junk Publishers.

Spatial and temporal variability of lightings over Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Matsangouras, J. T.

2010-09-01

Lightings are the most powerful and spectacular natural phenomena in the lower atmosphere, being a major cause of storm related deaths. Cloud-to-ground lightning can kill and injure people by direct or indirect means. Lightning affects the many electrochemical systems in the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. In this study, the spatial and temporal variability of recorded lightings over Greece during the period from January 1, 2008 to December 31, 2009, were analyzed. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS) archive dataset. An operational lighting detector network was established in 2007 by HNMS consisted of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. The spatial variability of lightings revealed their incidence within specific geographical sub-regions while the temporal variability concerning the seasonal, monthly and daily distributions resulted in better understanding of the time of lightings’ occurrence. All the analyses were carried out with respect to cloud to cloud, cloud to ground and ground to cloud lightings, within the examined time period.

A method for analyzing temporal patterns of variability of a time series from Poincare plots.

PubMed

Fishman, Mikkel; Jacono, Frank J; Park, Soojin; Jamasebi, Reza; Thungtong, Anurak; Loparo, Kenneth A; Dick, Thomas E

2012-07-01

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

Spatiotemporal changes in vegetation net primary productivity in the arid region of Northwest China, 2001 to 2012

NASA Astrophysics Data System (ADS)

Li, Zhen; Pan, Jinghu

2018-03-01

Net primary productivity (NPP) is recognized as an important index of ecosystem conditions and a key variable of the terrestrial carbon cycle. It also represents the comprehensive effects of climate change and anthropogenic activity on terrestrial vegetation. In this study, the temporal-spatial pattern of NPP for the period 2001-2012 was analyzed using a remote sensing-based carbon model (i.e., the Carnegie-Ames-Stanford Approach, CASA) in addition to other methods, such as linear trend analysis, standard deviation, and the Hurst index. Temporally, NPP showed a significant increasing trend for the arid region of Northwest China (ARNC), with an annual increase of 2.327 g C. Maximum and minimum productivity values appeared in July and December, respectively. Spatially, the NPP was relatively stable in the temperate and warm-temperate desert regions of Northwest China, while temporally, it showed an increasing trend. However, some attention should be given to the northwestern warm-temperate desert region, where there is severe continuous degradation and only a slight improvement trend.

Climatic change by cloudiness linked to the spatial variability of sea surface temperatures

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

An active role in modifying the earth's climate is suggested for low cloudiness over the circumarctic oceans. Such cloudiness, linked to the spatial differences in ocean surface temperatures, was studied. The temporal variations from year to year of ocean temperature patterns can be pronounced and therefore, the low cloudiness over this region should also show strong temporal variations, affecting the albedo of the earth and therefore the climate. Photographs are included.

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

NASA Technical Reports Server (NTRS)

Li, Bailing; Rodell, Matthew; Famiglietti, James S.

2015-01-01

Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.

Complex small pelagic fish population patterns arising from individual behavioral responses to their environment

NASA Astrophysics Data System (ADS)

Brochier, Timothée; Auger, Pierre-Amaël; Pecquerie, Laure; Machu, Eric; Capet, Xavier; Thiaw, Modou; Mbaye, Baye Cheikh; Braham, Cheikh-Baye; Ettahiri, Omar; Charouki, Najib; Sène, Ousseynou Ndaw; Werner, Francisco; Brehmer, Patrice

2018-05-01

Small pelagic fish (SPF) species are heavily exploited in eastern boundary upwelling systems (EBUS) as their transformation products are increasingly used in the world's food chain. Management relies on regular monitoring, but there is a lack of robust theories for the emergence of the populations' traits and their evolution in highly variable environments. This work aims to address existing knowledge gaps by combining physical and biogeochemical modelling with an individual life-cycle based model applied to round sardinella (Sardinella aurita) off northwest Africa, a key species for regional food security. Our approach focused on the processes responsible for seasonal migrations, spatio-temporal size-structure, and interannual biomass fluctuations. Emergence of preferred habitat resulted from interactions between natal homing behavior and environmental variability that impacts early life stages. Exploration of the environment by the fishes was determined by swimming capabilities, mesoscale to regional habitat structure, and horizontal currents. Fish spatio-temporal abundance variability emerged from a complex combination of distinct life-history traits. An alongshore gradient in fish size distributions is reported and validated by in situ measurements. New insights into population structure are provided, within an area where the species is abundant year-round (Mauritania) and with latitudinal migrations of variable (300-1200 km) amplitude. Interannual biomass fluctuations were linked to modulations of fish recruitment over the Sahara Bank driven by variability in alongshore current intensity. The identified processes constitute an analytical framework that can be implemented in other EBUS and used to explore impacts of regional climate change on SPF.

Relative contributions of mean-state shifts and ENSO-driven variability to precipitation changes in a warming climate

DOE PAGES

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; ...

2015-12-18

The El Niño–Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change.more » Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. Lastly, by examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.« less

A Search for Temporal Changes on Pluto and Charon

NASA Astrophysics Data System (ADS)

Hofgartner, Jason D.; Buratti, Bonnie J.; Devins, Spencer; Beyer, Ross A.; Schenk, Paul M.; Stern, S. Alan; Weaver, Harold A.; Olkin, Catherine; Cheng, Andrew F.; Ennico, Kimberly; Lauer, Tod R.; Spencer, John R.; Young, Leslie; New Horizons Science Team

2017-10-01

A search for temporal changes on Pluto and Charon was motivated by (1) the discovery of young surfaces in the Pluto system that imply ongoing or recent geologic activity, (2) the detection of active plumes on Triton during the Voyager 2 flyby, and (3) the abundant and detailed information that observing geologic processes in action provides about the processes. A thorough search for temporal changes using New Horizons images was completed. Images that covered the same region were blinked and manually inspected for any differences in appearance. The search included full-disk images such that all illuminated regions of both bodies were investigated and also higher resolution images such that parts of the encounter hemispheres were investigated at finer spatial scales. Changes of appearance between different images were observed but in all cases were attributed to variability of the imaging parameters (especially geometry) or artifacts. No differences of appearance that are strongly indicative of a temporal change were found on the surface or in the atmosphere of either Pluto or Charon. Limits on temporal changes as a function of spatial scale and temporal interval during the New Horizons encounter are determined. The longest time interval constraint is one Pluto/Charon rotation period (~6.4 Earth days). Contrast reversal and high-phase bright features that change in appearance with solar phase angle are identified. The change of appearance of these features is most likely due to the change in phase angle rather than a temporal change. Had active plumes analogous to the plumes discovered on Triton been present on the encounter hemispheres of either Pluto or Charon, they would have been detected. Several dark streak features that may be deposits from past plumes are identified. The absence of active plumes may be due to temporal variability or because the process that generates Triton’s plumes does not occur on Pluto.

A search for temporal changes on Pluto and Charon

NASA Astrophysics Data System (ADS)

Hofgartner, J. D.; Buratti, B. J.; Devins, S. L.; Beyer, R. A.; Schenk, P.; Stern, S. A.; Weaver, H. A.; Olkin, C. B.; Cheng, A.; Ennico, K.; Lauer, T. R.; McKinnon, W. B.; Spencer, J.; Young, L. A.; New Horizons Science Team

2018-03-01

A search for temporal changes on Pluto and Charon was motivated by (1) the discovery of young surfaces in the Pluto system that imply ongoing or recent geologic activity, (2) the detection of active plumes on Triton during the Voyager 2 flyby, and (3) the abundant and detailed information that observing geologic processes in action provides about the processes. A thorough search for temporal changes using New Horizons images was completed. Images that covered the same region were blinked and manually inspected for any differences in appearance. The search included full-disk images such that all illuminated regions of both bodies were investigated and higher resolution images such that parts of the encounter hemispheres were investigated at finer spatial scales. Changes of appearance between different images were observed but in all cases were attributed to variability of the imaging parameters (especially geometry) or artifacts. No differences of appearance that are strongly indicative of a temporal change were found on the surface or in the atmosphere of either Pluto or Charon. Limits on temporal changes as a function of spatial scale and temporal interval during the New Horizons encounter are determined. The longest time interval constraint is one Pluto/Charon rotation period (∼6.4 Earth days). Contrast reversal and high-phase bright features that change in appearance with solar phase angle are identified. The change of appearance of these features is most likely due to the change in phase angle rather than a temporal change. Had active plumes analogous to the plumes discovered on Triton been present on the encounter hemispheres of either Pluto or Charon, they would have been detected. The absence of active plumes may be due to temporal variability (i.e., plumes do occur but none were active on the encounter hemispheres during the epoch of the New Horizons encounter) or because plumes do not occur. Several dark streak features that may be deposits from past plumes are identified.

Climate variability in the subarctic area for the last 2 millennia

NASA Astrophysics Data System (ADS)

Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.

2018-01-01

To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.

Spectro-Temporal Weighting of Loudness

PubMed Central

Oberfeld, Daniel; Heeren, Wiebke; Rennies, Jan; Verhey, Jesko

2012-01-01

Real-world sounds like speech or traffic noise typically exhibit spectro-temporal variability because the energy in different spectral regions evolves differently as a sound unfolds in time. However, it is currently not well understood how the energy in different spectral and temporal portions contributes to loudness. This study investigated how listeners weight different temporal and spectral components of a sound when judging its overall loudness. Spectral weights were measured for the combination of three loudness-matched narrowband noises with different center frequencies. To measure temporal weights, 1,020-ms stimuli were presented, which randomly changed in level every 100 ms. Temporal weights were measured for each narrowband noise separately, and for a broadband noise containing the combination of the three noise bands. Finally, spectro-temporal weights were measured with stimuli where the level of the three narrowband noises randomly and independently changed every 100 ms. The data consistently showed that (i) the first 300 ms of the sounds had a greater influence on overall loudness perception than later temporal portions (primacy effect), and (ii) the lowest noise band contributed significantly more to overall loudness than the higher bands. The temporal weights did not differ between the three frequency bands. Notably, the spectral weights and temporal weights estimated from the conditions with only spectral or only temporal variability were very similar to the corresponding weights estimated in the spectro-temporal condition. The results indicate that the temporal and the spectral weighting of the loudness of a time-varying sound are independent processes. The spectral weights remain constant across time, and the temporal weights do not change across frequency. The results are discussed in the context of current loudness models. PMID:23209670

Brain regions and functional interactions supporting early word recognition in the face of input variability.

PubMed

Benavides-Varela, Silvia; Siugzdaite, Roma; Gómez, David Maximiliano; Macagno, Francesco; Cattarossi, Luigi; Mehler, Jacques

2017-07-18

Perception and cognition in infants have been traditionally investigated using habituation paradigms, assuming that babies' memories in laboratory contexts are best constructed after numerous repetitions of the very same stimulus in the absence of interference. A crucial, yet open, question regards how babies deal with stimuli experienced in a fashion similar to everyday learning situations-namely, in the presence of interfering stimuli. To address this question, we used functional near-infrared spectroscopy to test 40 healthy newborns on their ability to encode words presented in concomitance with other words. The results evidenced a habituation-like hemodynamic response during encoding in the left-frontal region, which was associated with a progressive decrement of the functional connections between this region and the left-temporal, right-temporal, and right-parietal regions. In a recognition test phase, a characteristic neural signature of recognition recruited first the right-frontal region and subsequently the right-parietal ones. Connections originating from the right-temporal regions to these areas emerged when newborns listened to the familiar word in the test phase. These findings suggest a neural specialization at birth characterized by the lateralization of memory functions: the interplay between temporal and left-frontal regions during encoding and between temporo-parietal and right-frontal regions during recognition of speech sounds. Most critically, the results show that newborns are capable of retaining the sound of specific words despite hearing other stimuli during encoding. Thus, habituation designs that include various items may be as effective for studying early memory as repeated presentation of a single word.

Indices of climate change in the Artic zone derived from radiosondes

NASA Astrophysics Data System (ADS)

Añel, J. A.; Gimeno, L.; de La Torre, L.; Nieto, R.; Tesouro, M.; Ribera, P.; García, R.; Hernández, E.

2003-04-01

The use of indices has been traditionally one of the main tools to identify climatic change. Here we present a study of the interannual variability of parameters derived from radiosonde data to study climate change in the artic zone. Trends, oscillations and the relationship with the principal climate variability mode for this region ( Northern Annular Mode) have been studied. We calculate the indices from the Upper Air Digital Files of the National Climatic Data Center (CARDS). We chose for our work the radiosonde data of stations over the studied region, with a temporal coverage of 27 years (1973-1998).

Spatial And Temporal Patterns As Well As Major Influencing Factors Of Global And Diffuse Horizontal Irradiance Over China: 1960-2014

NASA Astrophysics Data System (ADS)

Wang, H.; Sun, F.

2017-12-01

Global Horizontal Irradiance (GHI) on Earth is a central element of climate systems. With changes in the climate and regional development, the patterns and influencing factors of GHI, in addition to presenting global consistency, are increasingly showing regional particularities. Based on data for GHI, Diffuse Horizontal Irradiance (DHI) and potential impact factors (geographical position, elevation, cloud cover, water vapor, and ground atmospheric transparency related variables) from 1960 to 2014 in China, we analyzed the pattern and major influencing factors of GHI and DHI. The results showed that the major influencing factors of the GHI spatial pattern were the total cloud cover (TCC) and relative humidity (RH) in China. Dividing all of China into two regions, the major factors were the water vapor pressure (WVP) in the northern region and TCC in the southern region. And we divided the GHI and DHI data into two periods (1960-1987 and 1988-2014) due to global dimming and brightening observed in China in the late 1980's. The temporal GHI showed that 31 of 58 decreased significantly with an average decreasing rate of 95 MJ.10yr-1 during the periods of 1960-2014 and 49 of 76 stations decreased significantly with an rate of 342 MJ.10yr-1 during 1960-1987, whereas 57 of 88 stations did not change and 24 stations increased significantly with an rate of 201 MJ.10yr-1 during the period of 1988-2014. The temporal DHI showed that 40 of 61sites did not change significantly from 1960 to 1987. The major influencing factors for temporal changes of GHI in nine typical cities from 1960 to 2013 were as follows: air quality-related variables in super cities, sandstorms and wind in desert oasis cities, clouds in cities with good air quality and a low cloud amount (LCA) and annual fog days (FD) in Chengdu. Overall, we identified characteristics of GHI and DHI based on global climate change and regional urban development and found that the spatial characteristics of GHI results for China are consistent with global trends, whereas the spatial characteristics of DHI and temporal characteristics of GHI and DHI have changed significantly.

Fire Patterns and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2015-12-01

The West African tropical forest (referred to as the Upper Guinean forest, UGF), is a global biodiversity hotspot providing vital ecosystem services for the region's socio-economic and environmental wellbeing. It is also one of the most fragmented and human-modified tropical forest ecosystems, with the only remaining large patches of original forests contained in protected areas. However, these remnant forests are susceptible to continued fire-mediated degradation and forest loss due to intense climatic, demographic and land use pressures. We analyzed human and climatic drivers of fire activity in the sub-region to better understand the spatial and temporal patterns of these risks. We utilized MODIS active fire and burned area products to identify fire activity within the sub-region. We measured climatic variability using TRMM rainfall data and derived indicators of human land use from a variety of geospatial datasets. We used a boosted regression trees model to determine the influences of predictor variables on fire activity. Our analyses indicated that the spatial and temporal variability of precipitation is a key driving factor of fire activity in the UGF. Anthropogenic effects on fire activity in the area were evident through the influences of agriculture and low-density populations. These human footprints in the landscape make forests more susceptible to fires through forest fragmentation, degradation, and fire spread from agricultural areas. Forested protected areas within the forest savanna mosaic experienced frequent fires, whereas the more humid forest areas located in the south and south-western portions of the study area had fewer fires as these rainforests tend to offer some buffering against fire encroachment. These results improve characterization of UGF fire regime and expand our understanding of the spatio-temporal dynamics of tropical forest fires in response to human and climatic pressures.

Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric.

PubMed

Kuhn, T; Gullett, J M; Nguyen, P; Boutzoukas, A E; Ford, A; Colon-Perez, L M; Triplett, W; Carney, P R; Mareci, T H; Price, C C; Bauer, R M

2016-06-01

This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.

Probing the Quiet Solar Atmosphere from the Photosphere to the Corona

NASA Astrophysics Data System (ADS)

Kontogiannis, Ioannis; Gontikakis, Costis; Tsiropoula, Georgia; Tziotziou, Kostas

2018-04-01

We investigate the morphology and temporal variability of a quiet-Sun network region in different solar layers. The emission in several extreme ultraviolet (EUV) spectral lines through both raster and slot time-series, recorded by the EUV Imaging Spectrometer (EIS) on board the Hinode spacecraft is studied along with Hα observations and high-resolution spectropolarimetric observations of the photospheric magnetic field. The photospheric magnetic field is extrapolated up to the corona, showing a multitude of large- and small-scale structures. We show for the first time that the smallest magnetic structures at both the network and internetwork contribute significantly to the emission in EUV lines, with temperatures ranging from 8× 104 K to 6× 105 K. Two components of transition region emission are present, one associated with small-scale loops that do not reach coronal temperatures, and another component that acts as an interface between coronal and chromospheric plasma. Both components are associated with persistent chromospheric structures. The temporal variability of the EUV intensity at the network region is also associated with chromospheric motions, pointing to a connection between transition region and chromospheric features. Intensity enhancements in the EUV transition region lines are preferentially produced by Hα upflows. Examination of two individual chromospheric jets shows that their evolution is associated with intensity variations in transition region and coronal temperatures.

Understanding Atmospheric Anomalies Associated With Seasonal Pluvial-Drought Processes Using Southwest China as an Example

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2017-11-01

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution or spatial patterns of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key procedures and results include the following: (1) Because regional atmospheric variables are more directly responsible for the transition processes, we investigate it in detail. The temporal evolution of net vertical integral water vapor flux (net VIWVF) across SWC, together with vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω), coincides well with pluvial-drought transition processes. (2) With respect to large-scale circulation patterns, a well-organized Eurasian (EU) Pattern is one important feature during the pluvial-drought transitions over SWC. (3) Based on these large-scale and regional atmospheric anomalous features, relevant SA-based indices were built, to explore the possibility of simulating drought development using previous pluvial anomalies. As a whole, simulated drought development only with SA-based indices of large-scale circulation patterns does not perform well. Further, it can be improved a lot when SA-based indices of regional D and net VIWVF are introduced. (4) In addition, the potential drought prediction using pluvial anomalies, together with the deep understanding of physical mechanisms responsible for pluvial-drought transitions, need to be further explored.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

Growns, Ivor; Astles, Karen; Gehrke, Peter

2006-03-01

We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

Evaluating the spatiotemporal variations of water budget across China over 1951-2006 using IBIS model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Wei, X.; Peng, C.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.; Ju, W.

2010-01-01

The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run-off and actual evapotranspiration (AET)] of the water balance across China for the period 1951–2006 including a precipitation analysis. Results suggest three major findings. First, simulated run-off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash–Sutcliffe coefficients indicated that the quantity pattern of run-off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run-off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run-off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann–Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run-off, and the Zhemin hydrological region showed a significant increasing trend.

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

Spatial and temporal variability in greenhouse gas abundance of urban streams: The role of urban infrastructure

EPA Science Inventory

Background/Question/MethodsStreams and rivers are significant sources of greenhouse gas emissions globally. Water quality and watershed management, are likely to influence GHG emissions regionally. In urban-impacted watersheds, increased nitrogen loading, organic matter, and war...

Spatio-temporal variations of nitric acid total columns from 9 years of IASI measurements - a driver study

NASA Astrophysics Data System (ADS)

Ronsmans, Gaétane; Wespes, Catherine; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François

2018-04-01

This study aims to understand the spatial and temporal variability of HNO3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008-2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions which are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the Northern Hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the those defined as significant (p value < 0.05) by a selection algorithm are retained for each equivalent latitude band. Overall, the regression gives a good representation of HNO3 variability, with especially good results at high latitudes (60-80 % of the observed variability explained by the model). The regressions show the dominance of annual variability in all latitudinal bands, which is related to specific chemistry and dynamics depending on the latitudes. We find that the polar stratospheric clouds (PSCs) also have a major influence in the polar regions, and that their inclusion in the model improves the correlation coefficients and the residuals. However, there is still a relatively large portion of HNO3 variability that remains unexplained by the model, especially in the intertropical regions, where factors not included in the regression model (such as vegetation fires or lightning) may be at play.

Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe

NASA Astrophysics Data System (ADS)

Scheifinger, Helfried; Menzel, Annette; Koch, Elisabeth; Peter, Christian; Ahas, Rein

2002-11-01

A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed decoupling mechanism. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal variability from the influence of the westerly flow regime (local-scale loss of influence). This study corroborates an increasing number of similar investigations that find that vegetation does react in a sensitive way to variations of its atmospheric environment across various temporal and spatial scales.

Historical drought patterns over Canada and their teleconnections with large-scale climate signals

NASA Astrophysics Data System (ADS)

Asong, Zilefac Elvis; Wheater, Howard Simon; Bonsal, Barrie; Razavi, Saman; Kurkute, Sopan

2018-06-01

Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950-2013. The Mann-Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified - the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific-North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

Constraining regional scale carbon budgets at the US West Coast using a high-resolution atmospheric inverse modeling approach

NASA Astrophysics Data System (ADS)

Goeckede, M.; Michalak, A. M.; Vickers, D.; Turner, D.; Law, B.

2009-04-01

The study presented is embedded within the NACP (North American Carbon Program) West Coast project ORCA2, which aims at determining the regional carbon balance of the US states Oregon, California and Washington. Our work specifically focuses on the effect of disturbance history and climate variability, aiming at improving our understanding of e.g. drought stress and stand age on carbon sources and sinks in complex terrain with fine-scale variability in land cover types. The ORCA2 atmospheric inverse modeling approach has been set up to capture flux variability on the regional scale at high temporal and spatial resolution. Atmospheric transport is simulated coupling the mesoscale model WRF (Weather Research and Forecast) with the STILT (Stochastic Time Inverted Lagrangian Transport) footprint model. This setup allows identifying sources and sinks that influence atmospheric observations with highly resolved mass transport fields and realistic turbulent mixing. Terrestrial biosphere carbon fluxes are simulated at spatial resolutions of up to 1km and subdaily timesteps, considering effects of ecoregion, land cover type and disturbance regime on the carbon budgets. Our approach assimilates high-precision atmospheric CO2 concentration measurements and eddy-covariance data from several sites throughout the model domain, as well as high-resolution remote sensing products (e.g. LandSat, MODIS) and interpolated surface meteorology (DayMet, SOGS, PRISM). We present top-down modeling results that have been optimized using Bayesian inversion, reflecting the information on regional scale carbon processes provided by the network of high-precision CO2 observations. We address the level of detail (e.g. spatial and temporal resolution) that can be resolved by top-down modeling on the regional scale, given the uncertainties introduced by various sources for model-data mismatch. Our results demonstrate the importance of accurate modeling of carbon-water coupling, with the representation of water availability and drought stress playing a dominant role to capture spatially variable CO2 exchange rates in a region characterized by strong climatic gradients.

Impacts of cattle grazing on spatio-temporal variability of soil moisture and above-ground live plant biomass in mixed grasslands

NASA Astrophysics Data System (ADS)

Virk, Ravinder

Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB heterogeneity over time was observed for heavy grazing intensity. All grazing intensities showed decrease in spatial range (patch size) over time indicating that grazing is a patchy process. The study demonstrates that cattle grazing with variable intensity can maintain and change the spatial patterns of vegetation in the studied region. Using a modelling approach, the relative degrees to which grazing intensity and soil properties affect grassland productivity and carbon dynamics at longer time-periods were investigated. Both grass productivity and carbon dynamics are sensitive to variability in soil texture and grazing intensity. Moderate grazing is predicted to be the best option in terms of maintaining sufficient heterogeneity to support species diversity, as well as for carbon management in the mixed grassland ecosystem.

An architecture for encoding sentence meaning in left mid-superior temporal cortex

PubMed Central

Frankland, Steven M.; Greene, Joshua D.

2015-01-01

Human brains flexibly combine the meanings of words to compose structured thoughts. For example, by combining the meanings of “bite,” “dog,” and “man,” we can think about a dog biting a man, or a man biting a dog. Here, in two functional magnetic resonance imaging (fMRI) experiments using multivoxel pattern analysis (MVPA), we identify a region of left mid-superior temporal cortex (lmSTC) that flexibly encodes “who did what to whom” in visually presented sentences. We find that lmSTC represents the current values of abstract semantic variables (“Who did it?” and “To whom was it done?”) in distinct subregions. Experiment 1 first identifies a broad region of lmSTC whose activity patterns (i) facilitate decoding of structure-dependent sentence meaning (“Who did what to whom?”) and (ii) predict affect-related amygdala responses that depend on this information (e.g., “the baby kicked the grandfather” vs. “the grandfather kicked the baby”). Experiment 2 then identifies distinct, but neighboring, subregions of lmSTC whose activity patterns carry information about the identity of the current “agent” (“Who did it?”) and the current “patient” (“To whom was it done?”). These neighboring subregions lie along the upper bank of the superior temporal sulcus and the lateral bank of the superior temporal gyrus, respectively. At a high level, these regions may function like topographically defined data registers, encoding the fluctuating values of abstract semantic variables. This functional architecture, which in key respects resembles that of a classical computer, may play a critical role in enabling humans to flexibly generate complex thoughts. PMID:26305927

Analysis of streamflow variability in Alpine catchments at multiple spatial and temporal scales

NASA Astrophysics Data System (ADS)

Pérez Ciria, T.; Chiogna, G.

2017-12-01

Alpine watersheds play a pivotal role in Europe for water provisioning and for hydropower production. In these catchments, temporal fluctuations of river discharge occur at multiple temporal scales due to natural as well as anthropogenic driving forces. In the last decades, modifications of the flow regime have been observed and their origin lies in the complex interplay between construction of dams for hydro power production, changes in water management policies and climatic changes. The alteration of the natural flow has negative impacts on the freshwater biodiversity and threatens the ecosystem integrity of the Alpine region. Therefore, understanding the temporal and spatial variability of river discharge has recently become a particular concern for environmental protection and represents a crucial contribution to achieve sustainable water resources management in the Alps. In this work, time series analysis is conducted for selected gauging stations in the Inn and the Adige catchments, which cover a large part of the central and eastern region of the Alps. We analyze the available time series using the continuous wavelet transform and change-point analyses for determining how and where changes have taken place. Although both catchments belong to different climatic zones of the Greater Alpine Region, streamflow properties share some similar characteristics. The comparison of the collected streamflow time series in the two catchments permits detecting gradients in the hydrological system dynamics that depend on station elevation, longitudinal location in the Alps and catchment area. This work evidences that human activities (e.g., water management practices and flood protection measures, changes in legislation and market regulation) have major impacts on streamflow and should be rigorously considered in hydrological models.

Independent variable complexity for regional regression of the flow duration curve in ungauged basins

NASA Astrophysics Data System (ADS)

Fouad, Geoffrey; Skupin, André; Hope, Allen

2016-04-01

The flow duration curve (FDC) is one of the most widely used tools to quantify streamflow. Its percentile flows are often required for water resource applications, but these values must be predicted for ungauged basins with insufficient or no streamflow data. Regional regression is a commonly used approach for predicting percentile flows that involves identifying hydrologic regions and calibrating regression models to each region. The independent variables used to describe the physiographic and climatic setting of the basins are a critical component of regional regression, yet few studies have investigated their effect on resulting predictions. In this study, the complexity of the independent variables needed for regional regression is investigated. Different levels of variable complexity are applied for a regional regression consisting of 918 basins in the US. Both the hydrologic regions and regression models are determined according to the different sets of variables, and the accuracy of resulting predictions is assessed. The different sets of variables include (1) a simple set of three variables strongly tied to the FDC (mean annual precipitation, potential evapotranspiration, and baseflow index), (2) a traditional set of variables describing the average physiographic and climatic conditions of the basins, and (3) a more complex set of variables extending the traditional variables to include statistics describing the distribution of physiographic data and temporal components of climatic data. The latter set of variables is not typically used in regional regression, and is evaluated for its potential to predict percentile flows. The simplest set of only three variables performed similarly to the other more complex sets of variables. Traditional variables used to describe climate, topography, and soil offered little more to the predictions, and the experimental set of variables describing the distribution of basin data in more detail did not improve predictions. These results are largely reflective of cross-correlation existing in hydrologic datasets, and highlight the limited predictive power of many traditionally used variables for regional regression. A parsimonious approach including fewer variables chosen based on their connection to streamflow may be more efficient than a data mining approach including many different variables. Future regional regression studies may benefit from having a hydrologic rationale for including different variables and attempting to create new variables related to streamflow.

Mountain Hydrology of the Semi-Arid Western U.S.: Research Needs, Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Bales, R.; Dozier, J.; Molotch, N.; Painter, T.; Rice, R.

2004-12-01

In the semi-arid Western U.S., water resources are being stressed by the combination of climate warming, changing land use, and population growth. Multiple consensus planning documents point to this region as perhaps the highest priority for new hydrologic understanding. Three main hydrologic issues illustrate research needs in the snow-driven hydrology of the region. First, despite the hydrologic importance of mountainous regions, the processes controlling their energy, water and biogeochemical fluxes are not well understood. Second, there exists a need to realize, at various spatial and temporal scales, the feedback systems between hydrological fluxes and biogeochemical and ecological processes. Third, the paucity of adequate observation networks in mountainous regions hampers improvements in understanding these processes. For example, we lack an adequate description of factors controlling the partitioning of snowmelt into runoff versus infiltration and evapotranspiration, and need strategies to accurately measure the variability of precipitation, snow cover and soil moisture. The amount of mountain-block and mountain-front recharge and how recharge patterns respond to climate variability are poorly known across the mountainous West. Moreover, hydrologic modelers and those measuring important hydrologic variables from remote sensing and distributed in situ sites have failed to bridge rifts between modeling needs and available measurements. Research and operational communities will benefit from data fusion/integration, improved measurement arrays, and rapid data access. For example, the hydrologic modeling community would advance if given new access to single rather than disparate sources of bundles of cutting-edge remote sensing retrievals of snow covered area and albedo, in situ measurements of snow water equivalent and precipitation, and spatio-temporal fields of variables that drive models. In addition, opportunities exist for the deployment of new technologies, taking advantage of research in spatially distributed sensor networks that can enhance data recovery and analysis.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Investigatigating inter-/intra-annual variability of surface hydrology at northern high latitude from spaceborne measurements

NASA Astrophysics Data System (ADS)

Kang, K.; Duguay, C. R.

2014-12-01

Lakes encompass a large part of the surface cover in the northern boreal and tundra areas of northern Canada and are therefore a significant component of the terrestrial hydrological system. To understand the hydrologic cycle over subarctic and arctic landscapes, estimating surface parameters such as surface net radiation, soil moisture, and surface albedo is important. Although ground-based field measurements provide a good temporal resolution, these data provide a limited spatial representation and are often restricted to the summer period (from June to August), and few surface-based stations are located in high-latitude regions. In this respect, spaceborne remote sensing provides the means to monitor surface hydrology and to estimate components of the surface energy balance with reasonable spatial and temporal resolutions required for hydrological investigations, as well as for providing more spatially representative lake-relevant information than available from in situ measurements. The primary objective of this study is to quantify the sources of temporal and spatial variability in surface albedo over subarctic wetland from satellite derived albedo measurements in the Hudson Bay Lowlands near Churchill, Manitoba. The spatial variability in albedo within each land-cover type is investigated through optical satellite imagery from Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper Plus, and Landsat-8 Operational Land Imager obtained in different seasons from spring into fall (April and October) over a 30-year period (1984-2013). These data allowed for an examination of the spatial variability of surface albedo under relatively dry and wet summer conditions (i.e. 1984, 1998 versus 1991, 2005). A detailed analysis of Landsat-derived surface albedo (ranging from 0.09 to 0.15) conducted in the Churchill region for August is inversely related to surface water fraction calculated from Landsat images. Preliminary analysis of surface albedo observed between July and August are 0.10 to 0.15, and vary due to differences in meteorological parameters such as rainfall, surface moisture and surface air temperature. Overall, spaceborne optical data are an invaluable source for investigating changes and variability in surface albedo in relation to surface hydrology over subarctic regions.

Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

NASA Technical Reports Server (NTRS)

Stramski, Dariusz; Stramska, Malgorzata

2005-01-01

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions.

Landscape fragmentation affects responses of avian communities to climate change.

PubMed

Jarzyna, Marta A; Porter, William F; Maurer, Brian A; Zuckerberg, Benjamin; Finley, Andrew O

2015-08-01

Forecasting the consequences of climate change is contingent upon our understanding of the relationship between biodiversity patterns and climatic variability. While the impacts of climate change on individual species have been well-documented, there is a paucity of studies on climate-mediated changes in community dynamics. Our objectives were to investigate the relationship between temporal turnover in avian biodiversity and changes in climatic conditions and to assess the role of landscape fragmentation in affecting this relationship. We hypothesized that community turnover would be highest in regions experiencing the most pronounced changes in climate and that these patterns would be reduced in human-dominated landscapes. To test this hypothesis, we quantified temporal turnover in avian communities over a 20-year period using data from the New York State Breeding Atlases collected during 1980-1985 and 2000-2005. We applied Bayesian spatially varying intercept models to evaluate the relationship between temporal turnover and temporal trends in climatic conditions and landscape fragmentation. We found that models including interaction terms between climate change and landscape fragmentation were superior to models without the interaction terms, suggesting that the relationship between avian community turnover and changes in climatic conditions was affected by the level of landscape fragmentation. Specifically, we found weaker associations between temporal turnover and climatic change in regions with prevalent habitat fragmentation. We suggest that avian communities in fragmented landscapes are more robust to climate change than communities found in contiguous habitats because they are comprised of species with wider thermal niches and thus are less susceptible to shifts in climatic variability. We conclude that highly fragmented regions are likely to undergo less pronounced changes in composition and structure of faunal communities as a result of climate change, whereas those changes are likely to be greater in contiguous and unfragmented habitats. © 2015 John Wiley & Sons Ltd.

Sea ice concentration temporal variability over the Weddell Sea and its relationship with tropical sea surface temperature

USGS Publications Warehouse

Barreira, S.; Compagnucci, R.

2007-01-01

Principal Components Analysis (PCA) in S-Mode (correlation between temporal series) was performed on sea ice monthly anomalies, in order to investigate which are the main temporal patterns, where are the homogenous areas located and how are they related to the sea surface temperature (SST). This analysis provides 9 patterns (4 in the Amundsen and Bellingshausen Seas and 5 in the Weddell Sea) that represent the most important temporal features that dominated sea ice concentration anomalies (SICA) variability in the Weddell, Amundsen and Bellingshausen Seas over the 1979-2000 period. Monthly Polar Gridded Sea Ice Concentrations data set derived from satellite information generated by NASA Team algorithm and acquired from the National Snow and Ice Data Center (NSIDC) were used. Monthly means SST are provided by the National Center for Environmental Prediction reanalysis. The first temporal pattern series obtained by PCA has its homogeneous area located at the external region of the Weddell and Bellingshausen Seas and Drake Passage, mostly north of 60°S. The second region is centered in 30°W and located at the southeast of the Weddell. The third area is localized east of 30°W and north of 60°S. South of the first area, the fourth PC series has its homogenous region, between 30° and 60°W. The last area is centered at 0° W and south of 60°S. Correlation charts between the five Principal Components series and SST were performed. Positive correlations over the Tropical Pacific Ocean were found for the five PCs when SST series preceded SICA PC series. The sign of the correlation could relate the occurrence of an El Niño/Southern Oscillation (ENSO) warm (cold) event with posterior positive (negative) anomalies of sea ice concentration over the Weddell Sea.

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatiotemporal characteristics of heat waves over China in regional climate simulations within the CORDEX-EA project

NASA Astrophysics Data System (ADS)

Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang

2018-03-01

Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances.

Assessing Global Water Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal Anomalies and Extremes.

PubMed

Humphrey, Vincent; Gudmundsson, Lukas; Seneviratne, Sonia I

Throughout the past decade, the Gravity Recovery and Climate Experiment (GRACE) has given an unprecedented view on global variations in terrestrial water storage. While an increasing number of case studies have provided a rich overview on regional analyses, a global assessment on the dominant features of GRACE variability is still lacking. To address this, we survey key features of temporal variability in the GRACE record by decomposing gridded time series of monthly equivalent water height into linear trends, inter-annual, seasonal, and subseasonal (intra-annual) components. We provide an overview of the relative importance and spatial distribution of these components globally. A correlation analysis with precipitation and temperature reveals that both the inter-annual and subseasonal anomalies are tightly related to fluctuations in the atmospheric forcing. As a novelty, we show that for large regions of the world high-frequency anomalies in the monthly GRACE signal, which have been partly interpreted as noise, can be statistically reconstructed from daily precipitation once an adequate averaging filter is applied. This filter integrates the temporally decaying contribution of precipitation to the storage changes in any given month, including earlier precipitation. Finally, we also survey extreme dry anomalies in the GRACE record and relate them to documented drought events. This global assessment sets regional studies in a broader context and reveals phenomena that had not been documented so far.

Spatial-temporal bio-optical classification of dynamic semi-estuarine waters in western North America

NASA Astrophysics Data System (ADS)

Phillips, Stephen Robert; Costa, Maycira

2017-12-01

The use of standard ocean colour reflectance based algorithms to derive surface chlorophyll may have limited applicability for optically dynamic coastal waters due to the pre-defined coefficients based on global datasets. Reflectance based algorithms adjusted to regional optical water characteristics are a promising alternative. A class-based definition of optically diverse coastal waters was investigated as a first step towards the development of temporal and spatial constrained reflectance based algorithms for optically variable coastal waters. A large set of bio-optical data were collected as part of five research cruises and bi-weekly trips aboard a ship of opportunity in the west coast of Canada, to assess the spatial and temporal variability of above-water reflectance in this contrasted coastal environment. To accomplish this, in situ biophysical and optical measurements were collected in conjunction with above-water hyperspectral remote sensing reflectance (Rrs) at 145 stations. The concentrations of measured biophysical data varied considerably; chlorophyll a (Chla) (mean = 1.64, range: 0.10-7.20 μg l-1), total suspended matter (TSM) (3.09, 0.82-20.69 mg l-1), and absorption by chromophoric dissolved organic matter (CDOM) (acdom(443 nm)) (0.525, 0.007-3.072 m-1), thus representing the spatio-temporal variability of the Salish Sea. Optically, a similar large range was also found; particulate scattering (bp(650 nm)) (1.316, 0.250-7.450 m-1), particulate backscattering (bbp(650 nm)) (0.022, 0.005-0.097 m-1), total beam attenuation coefficient (ct(650)) (1.675, 0.371-9.537 m-1) and particulate absorption coefficient (ap(650 nm)) (0.345, 0.048-2.020 m-1). An empirical orthogonal function (EOF) analysis revealed that Rrs variability was highly correlated to bp (r = 0.90), bbp (r = 0.82) and concentration of TSM (r = 0.80), which highlighted the dominant role of water turbidity in this region. Hierarchical clustering analysis was applied to the normalized Rrs spectra to define optical water classes. Class 1 was defined by the highest Rrs values, particularly above 570 nm, indicating more turbid waters; Class 2 was dominated by high Chla and TSM concentrations, which is shown by high Rrs at 570 nm as well as fluorescence and absorption peaks; Class 3 shows strong fluorescence signatures accompanied by low TSM influence; and Class 4 is most representative of clear waters with a less defined absorption peak around 440 nm. By understanding the bio-optical factors which control the variability of the Rrs spectra this study aims to develop a sub-regional characterization of this coastal region aiming to improve bio-optical algorithms in this complex coastal area.

Simulated sensitivity of seasonal ozone exposure in the Great Lakes region to changes in anthropogenic emissions in the presence of interannual variability

Treesearch

Jerome D. Fast; Warren E. Heilman

2005-01-01

A coupled meteorological and chemical modeling system with a 12-km horizontal grid spacing was used to simulate the evolution of ozone over the Great Lakes region between May and September of 1999 and 2001. The overall temporal and spatial variations in hourly ozone concentrations and ozone exposure from control simulations agreed reasonably well with the observations...

Field-scale modeling of center pivot irrigated cotton: Oullman clay loam series

USDA-ARS?s Scientific Manuscript database

Regulatory ground water pumping restrictions continue to be debated in the Southern Ogallala Aquifer region and will eventually result in allocation of irrigation resources becoming more important. Models that address the temporal and spatial variability of water, energy, and nutrient balances at fi...

Cross-scale interactions drive ecosystem responses to precipitation in the Chihuahuan Desert

USDA-ARS?s Scientific Manuscript database

Regime shifts from grass- to shrub-dominated states are widespread in arid and semiarid regions globally. These patterns of grass production and shifts to shrub dominance are spatially variable and correlate weakly with precipitation, suggesting that processes at different spatial and temporal scale...

Spatial and Temporal Variation in the Effects of Climatic Variables on Dugong Calf Production

PubMed Central

Fuentes, Mariana M. P. B.; Delean, Steven; Grayson, Jillian; Lavender, Sally; Logan, Murray; Marsh, Helene

2016-01-01

Knowledge of the relationships between environmental forcing and demographic parameters is important for predicting responses from climatic changes and to manage populations effectively. We explore the relationships between the proportion of sea cows (Dugong dugon) classified as calves and four climatic drivers (rainfall anomaly, Southern Oscillation El Niño Index [SOI], NINO 3.4 sea surface temperature index, and number of tropical cyclones) at a range of spatially distinct locations in Queensland, Australia, a region with relatively high dugong density. Dugong and calf data were obtained from standardized aerial surveys conducted along the study region. A range of lagged versions of each of the focal climatic drivers (1 to 4 years) were included in a global model containing the proportion of calves in each population crossed with each of the lagged versions of the climatic drivers to explore relationships. The relative influence of each predictor was estimated via Gibbs variable selection. The relationships between the proportion of dependent calves and the climatic drivers varied spatially and temporally, with climatic drivers influencing calf counts at sub-regional scales. Thus we recommend that the assessment of and management response to indirect climatic threats on dugongs should also occur at sub-regional scales. PMID:27355367

Space-borne Chlorophyll Fluorescence, Greenness, Vegetation Models and Interannual Variability of Photosynthetic Activity: Spatio-temporal Patterns, Mechanisms, and Environmental Sensitivities

NASA Astrophysics Data System (ADS)

Walther, S.; Guanter, L.; Jung, M.; Frankenberg, C.; Sun, Y.; Forkel, M.; Zhang, Y.; Duveiller, G.; Cescatti, A.; Camps-Valls, G.; Köhler, P.

2016-12-01

It is much debated whether respiration or photosynthesis drive net ecosystem productivity andwhich regions contribute strongest to the observed interannual variability (IAV) of the strengthof the land sink. Several studies point to photosynthetic productivity in semi-arid regions as avery important factor influencing atmospheric CO2 variability globally (e.g. Jung et al., 2011;Poulter et al., 2014; Ahlstr ̈ om et al., 2015). Here, we aim at a comprehensive comparison ofthe strength, timing and spatial extent of anomalies of photosynthesis as they are indicated bysatellite observations of greenness, vegetation optical depth, and sun-induced chlorophyll fluo-rescence (SIF). We will compare them to the results of diagnostic, empirical and process-basedvegetation models. Except for the evergreen tropics, the spatio-temporal patterns of monthlydominant vegetation variability are generally consistently shown in semi-arid areas, albeit withdiffering magnitudes between greenness and photosynthesis globally. Relative anomalies (to themean seasonal cycle) are particularly widespread in high northern latitudes. Further researchsteps will include i) the repeated analysis at higher temporal resolution to better refine the dif-ferent time scales of reaction between light-use-efficiency and APAR and between forestedand non-forested ecosystems, ii) investigate on characteristic time scales at which the proxies(dis-)agree and why, iii) study the relative contributions of anomalies in peak and length of thegrowing season to IAV (similar to Xia et al., 2015; Zhou et al., 2016), iv) analyse the proxiesfor possibly differing hydrological sensitivities, and v) vegetation models have long been knownto have very diverse abilities to capture GPP IAV. Our preliminary results confirm this and wewill further study possible limitations and possible ways for improvement of the simulations.

Information content of MOPITT CO profile retrievals: Temporal and geographical variability

NASA Astrophysics Data System (ADS)

Deeter, M. N.; Edwards, D. P.; Gille, J. C.; Worden, H. M.

2015-12-01

Satellite measurements of tropospheric carbon monoxide (CO) enable a wide array of applications including studies of air quality and pollution transport. The MOPITT (Measurements of Pollution in the Troposphere) instrument on the Earth Observing System Terra platform has been measuring CO concentrations globally since March 2000. As indicated by the Degrees of Freedom for Signal (DFS), the standard metric for trace-gas retrieval information content, MOPITT retrieval performance varies over a wide range. We show that both instrumental and geophysical effects yield significant geographical and temporal variability in MOPITT DFS values. Instrumental radiance uncertainties, which describe random errors (or "noise") in the calibrated radiances, vary over long time scales (e.g., months to years) and vary between the four detector elements of MOPITT's linear detector array. MOPITT retrieval performance depends on several factors including thermal contrast, fine-scale variability of surface properties, and CO loading. The relative importance of these various effects is highly variable, as demonstrated by analyses of monthly mean DFS values for the United States and the Amazon Basin. An understanding of the geographical and temporal variability of MOPITT retrieval performance is potentially valuable to data users seeking to limit the influence of the a priori through data filtering. To illustrate, it is demonstrated that calculated regional-average CO mixing ratios may be improved by excluding observations from a subset of pixels in MOPITT's linear detector array.

Hot spots, hot moments and time-span of changes in drivers and their responses on carbon cycling in Europe

NASA Astrophysics Data System (ADS)

Tomelleri, E.; Forkel, M.; Fuchs, R.; Jung, M.; Mahecha, M. D.; Reichstein, M.; Weber, U.

2012-12-01

The objective of this study is to provide a complete quantitative assessment of the annual to decadal variability, hotspots of changes and the temporal magnitude of regional trends and variability for the main drivers of carbon cycle like climate and land use and their responses for Europe. For this purpose we used an harmonized climatic data set (ERA Interim and WATCH) and an historical land-use change reconstruction (HILDAv1, Fuchs in prep.). Both the data sets cover the period 1900-2010 and have a 0.25 deg spatial resolution. As driver response we used two different empirically up-scaled GPP fields: the first (MTE) obtained by the application of model trees (Jung et al. 2009) and a second (LUE) based on a light use efficiency model (Tomelleri in prep.). Both the approaches are based on the up-scaling of Fluxnet observations. The response fields have monthly temporal resolution and are limited to the period 1982-2011. We estimated break-points in time series of driver and response variables based on the method of Bai and Perron (2003) to identify changes in trends. This method was implemented in Verbesselt et al. 2010 and applied by deJong et al. 2011 to detect phenological and abrupt changes and trends in vegetation activity based on satellite-derived vegetation index time series. The analysis of drivers and responses allowed to identify the dominant factors driving the biosphere-atmosphere carbon exchange. The synchronous analysis of climatic drivers and land use change allowed us to explain most of the temporal and spatial variability showing that in the regions and time period where the most land use change occurred the climatic drivers are not sufficient to explain trends and oscillation in carbon cycling. The comparison of our analysis for the up-scaling methods shows some agreement: we found inconsistency in the spatial and temporal patterns in regions where the Fluxnet network is less dense. This can be explained by the conceptual difference in the up-scaling methods: while one is on pixel basis (MTE) the other (LUE) is up-scaling model parameters by bioclimatic regions. Our study shows the value of up-scaling methods for understanding the spatial-temporal variability of carbon cycling and how these are a valuable tool for spatial and temporal analysis. Furthermore, the use of climatic drivers and land-use change demonstrated the need of taking natural and anthropogenic drivers into consideration for explaining trends and oscillations. Possibly a further analysis including detailed management practices for forestry and agriculture would help in explaining the remaining variance. References: Bai, J., Perron, P.: Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 2003. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 2009. Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D.: Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment,114(1), 2010. de Jong, R., Verbesselt, J., Schaepman, M.E., Bruin, S.: Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Global Change Biology, 18, 2011.

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Springwater geochemistry at Honey Creek State Natural Area, central Texas: Implications for surface water and groundwater interaction in a karst aquifer

NASA Astrophysics Data System (ADS)

Musgrove, M.; Stern, L. A.; Banner, J. L.

2010-06-01

SummaryA two and a half year study of two adjacent watersheds at the Honey Creek State Natural Area (HCSNA) in central Texas was undertaken to evaluate spatial and temporal variations in springwater geochemistry, geochemical evolution processes, and potential effects of brush control on karst watershed hydrology. The watersheds are geologically and geomorphologically similar, and each has springs discharging into Honey Creek, a tributary to the Guadalupe River. Springwater geochemistry is considered in a regional context of aquifer components including soil water, cave dripwater, springwater, and phreatic groundwater. Isotopic and trace element variability allows us to identify both vadose and phreatic groundwater contributions to surface water in Honey Creek. Spatial and temporal geochemical data for six springs reveal systematic differences between the two watersheds. Springwater Sr isotope values lie between values for the limestone bedrock and soils at HCSNA, reflecting a balance between these two primary sources of Sr. Sr isotope values for springs within each watershed are consistent with differences between soil compositions. At some of the springs, consistent temporal variability in springwater geochemistry (Sr isotopes, Mg/Ca, and Sr/Ca values) appears to reflect changes in climatic and hydrologic parameters (rainfall/recharge) that affect watershed processes. Springwater geochemistry was unaffected by brush removal at the scale of the HCSNA study. Results of this study build on previous regional studies to provide insight into watershed hydrology and regional hydrologic processes, including connections between surface water, vadose groundwater, and phreatic groundwater.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

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

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Temporal Lobe and Frontal-Subcortical Dissociations in Non-Demented Parkinson's Disease with Verbal Memory Impairment.

PubMed

Tanner, Jared J; Mareci, Thomas H; Okun, Michael S; Bowers, Dawn; Libon, David J; Price, Catherine C

2015-01-01

The current investigation examined verbal memory in idiopathic non-dementia Parkinson's disease and the significance of the left entorhinal cortex and left entorhinal-retrosplenial region connections (via temporal cingulum) on memory impairment in Parkinson's disease. Forty non-demented Parkinson's disease patients and forty non-Parkinson's disease controls completed two verbal memory tests--a wordlist measure (Philadelphia repeatable Verbal Memory Test) and a story measure (Logical Memory). All participants received T1-weighted and diffusion magnetic resonance imaging (3T; Siemens) sequences. Left entorhinal volume and left entorhinal-retrosplenial connectivity (temporal cingulum edge weight) were the primary imaging variables of interest with frontal lobe thickness and subcortical structure volumes as dissociating variables. Individuals with Parkinson's disease showed worse verbal memory, smaller entorhinal volumes, but did not differ in entorhinal-retrosplenial connectivity. For Parkinson's disease entorhinal-retrosplenial edge weight had the strongest associations with verbal memory. A subset of Parkinson's disease patients (23%) had deficits (z-scores < -1.5) across both memory measures. Relative to non-impaired Parkinson's peers, this memory-impaired group had smaller entorhinal volumes. Although entorhinal cortex volume was significantly reduced in Parkinson's disease patients relative to non-Parkinson's peers, only white matter connections associated with the entorhinal cortex were significantly associated with verbal memory performance in our sample. There was also no suggestion of contribution from frontal-subcortical gray or frontal white matter regions. These findings argue for additional investigation into medial temporal lobe gray and white matter connectivity for understanding memory in Parkinson's disease.

Early Activation of Ventral Hippocampus and Subiculum during Spontaneous Seizures in a Rat Model of Temporal Lobe Epilepsy

PubMed Central

Toyoda, Izumi; Bower, Mark R.; Leyva, Fernando

2013-01-01

Temporal lobe epilepsy is the most common form of epilepsy in adults. The pilocarpine-treated rat model is used frequently to investigate temporal lobe epilepsy. The validity of the pilocarpine model has been challenged based largely on concerns that seizures might initiate in different brain regions in rats than in patients. The present study used 32 recording electrodes per rat to evaluate spontaneous seizures in various brain regions including the septum, dorsomedial thalamus, amygdala, olfactory cortex, dorsal and ventral hippocampus, substantia nigra, entorhinal cortex, and ventral subiculum. Compared with published results from patients, seizures in rats tended to be shorter, spread faster and more extensively, generate behavioral manifestations more quickly, and produce generalized convulsions more frequently. Similarities to patients included electrographic waveform patterns at seizure onset, variability in sites of earliest seizure activity within individuals, and variability in patterns of seizure spread. Like patients, the earliest seizure activity in rats was recorded most frequently within the hippocampal formation. The ventral hippocampus and ventral subiculum displayed the earliest seizure activity. Amygdala, olfactory cortex, and septum occasionally displayed early seizure latencies, but not above chance levels. Substantia nigra and dorsomedial thalamus demonstrated consistently late seizure onsets, suggesting their unlikely involvement in seizure initiation. The results of the present study reveal similarities in onset sites of spontaneous seizures in patients with temporal lobe epilepsy and pilocarpine-treated rats that support the model's validity. PMID:23825415

Temporal Changes in Community Resilience to Drought Hazard

NASA Astrophysics Data System (ADS)

Mihunov, V.

2017-12-01

The threat of droughts and their associated impacts on the landscape and human communities have long been recognized. While considerable research on the climatological aspect of droughts has been conducted, studies on the resilience of human communities to the effects of drought remain limited. Understanding how different communities respond to and recover from the drought hazard, i.e. their community resilience, should inform the development of better strategies to cope with the hazard. This research assesses community resilience to drought hazard in South-Central U.S. and captures the temporal changes of community resilience in the region facing the climate change. First, the study applies the Resilience Inference Measurement (RIM) framework using the existing drought incidence, crop damage, socio-economic and food-water-energy nexus variables, which allows to assign county-level resilience scores in the study region and derive variables contributing to the resilience. Second, it captures the temporal changes in community resilience by using the model extracted from the RIM study and socio-economic data from several consecutive time periods. The resilience measurement study should help understand the complex process underlying communities' response to the drought impacts. The results identify gaps in resilience planning and help the improvement of the community resilience to the droughts of increasing frequency and intensity.

Survival estimates for Florida manatees from the photo-identification of individuals

USGS Publications Warehouse

Langtimm, C.A.; Beck, C.A.; Edwards, H.H.; Fick-Child, K. J.; Ackerman, B.B.; Barton, S.L.; Hartley, W.C.

2004-01-01

We estimated adult survival probabilities for the endangered Florida manatee (Trichechus manatus latirostris) in four regional populations using photo-identification data and open-population capture-recapture statistical models. The mean annual adult survival probability over the most recent 10-yr period of available estimates was as follows: Northwest - 0.956 (SE 0.007), Upper St. Johns River - 0.960 (0.011), Atlantic Coast - 0.937 (0.008), and Southwest - 0.908 (0.019). Estimates of temporal variance independent of sampling error, calculated from the survival estimates, indicated constant survival in the Upper St. Johns River, true temporal variability in the Northwest and Atlantic Coast, and large sampling variability obscuring estimates for the Southwest. Calf and subadult survival probabilities were estimated for the Upper St. Johns River from the only available data for known-aged individuals: 0.810 (95% CI 0.727-0.873) for 1st year calves, 0.915 (0.827-0.960) for 2nd year calves, and 0.969 (0.946-0.982) for manatee 3 yr or older. These estimates of survival probabilities and temporal variance, in conjunction with estimates of reproduction probabilities from photoidentification data can be used to model manatee population dynamics, estimate population growth rates, and provide an integrated measure of regional status.

Fine-temporal forecasting of outbreak probability and severity: Ross River virus in Western Australia.

PubMed

Koolhof, I S; Bettiol, S; Carver, S

2017-10-01

Health warnings of mosquito-borne disease risk require forecasts that are accurate at fine-temporal resolutions (weekly scales); however, most forecasting is coarse (monthly). We use environmental and Ross River virus (RRV) surveillance to predict weekly outbreak probabilities and incidence spanning tropical, semi-arid, and Mediterranean regions of Western Australia (1991-2014). Hurdle and linear models were used to predict outbreak probabilities and incidence respectively, using time-lagged environmental variables. Forecast accuracy was assessed by model fit and cross-validation. Residual RRV notification data were also examined against mitigation expenditure for one site, Mandurah 2007-2014. Models were predictive of RRV activity, except at one site (Capel). Minimum temperature was an important predictor of RRV outbreaks and incidence at all predicted sites. Precipitation was more likely to cause outbreaks and greater incidence among tropical and semi-arid sites. While variable, mitigation expenditure coincided positively with increased RRV incidence (r 2 = 0·21). Our research demonstrates capacity to accurately predict mosquito-borne disease outbreaks and incidence at fine-temporal resolutions. We apply our findings, developing a user-friendly tool enabling managers to easily adopt this research to forecast region-specific RRV outbreaks and incidence. Approaches here may be of value to fine-scale forecasting of RRV in other areas of Australia, and other mosquito-borne diseases.

Climate and Southern Africa's Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Conway, D.; Osborn, T.; Dorling, S.; Ringler, C.; Lankford, B.; Dalin, C.; Thurlow, J.; Zhu, T.; Deryng, D.; Landman, W.; Archer van Garderen, E.; Krueger, T.; Lebek, K.

2014-12-01

Numerous challenges coalesce to make Southern Africa emblematic of the connections between climate and the water-energy-food nexus. Rainfall and river flows in the region show high levels of variability across a range of spatial and temporal scales. Physical and socioeconomic exposure to climate variability and change is high, for example, the contribution of electricity produced from hydroelectric sources is over 30% in Madagascar and Zimbabwe and almost 100% in the DRC, Lesotho, Malawi, and Zambia. The region's economy is closely linked with that of the rest of the African continent and climate-sensitive food products are an important item of trade. Southern Africa's population is concentrated in regions exposed to high levels of hydro-meteorological variability, and will increase rapidly over the next four decades. The capacity to manage the effects of climate variability tends, however, to be low. Moreover, with climate change annual precipitation levels, soil moisture and runoff are likely to decrease and rising temperatures will increase evaporative demand. Despite high levels of hydro-meteorological variability, the sectoral and cross-sectoral water-energy-food linkages with climate in Southern Africa have not been considered in detail. Lack of data and questionable reliability are compounded by complex dynamic relationships. We review the role of climate in Southern Africa's nexus, complemented by empirical analysis of national level data on climate, water resources, crop and energy production, and economic activity. Our aim is to examine the role of climate variability as a driver of production fluctuations in the nexus, and to improve understanding of the magnitude and temporal dimensions of their interactions. We first consider national level exposure of food, water and energy production to climate in aggregate economic terms and then examine the linkages between interannual and multi-year climate variability and economic activity, focusing on food and hydropower production. We then review the potential for connecting areas with robust seasonal climate forecasting skill with key precursors of economic output and conclude by identifying knowledge gaps in our understanding of regional and national economic linkages in the climate and water-energy-food nexus.

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.

Classification of Regional Ionospheric Disturbances Based on Support Vector Machines

NASA Astrophysics Data System (ADS)

Begüm Terzi, Merve; Arikan, Feza; Arikan, Orhan; Karatay, Secil

2016-07-01

Ionosphere is an anisotropic, inhomogeneous, time varying and spatio-temporally dispersive medium whose parameters can be estimated almost always by using indirect measurements. Geomagnetic, gravitational, solar or seismic activities cause variations of ionosphere at various spatial and temporal scales. This complex spatio-temporal variability is challenging to be identified due to extensive scales in period, duration, amplitude and frequency of disturbances. Since geomagnetic and solar indices such as Disturbance storm time (Dst), F10.7 solar flux, Sun Spot Number (SSN), Auroral Electrojet (AE), Kp and W-index provide information about variability on a global scale, identification and classification of regional disturbances poses a challenge. The main aim of this study is to classify the regional effects of global geomagnetic storms and classify them according to their risk levels. For this purpose, Total Electron Content (TEC) estimated from GPS receivers, which is one of the major parameters of ionosphere, will be used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. In this work, for the automated classification of the regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. SVM is a supervised learning model used for classification with associated learning algorithm that analyze the data and recognize patterns. In addition to performing linear classification, SVM can efficiently perform nonlinear classification by embedding data into higher dimensional feature spaces. Performance of the developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from the GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing the developed classification technique to the Global Ionospheric Map (GIM) TEC data which is provided by the NASA Jet Propulsion Laboratory (JPL), it will be shown that SVM can be a suitable learning method to detect the anomalies in Total Electron Content (TEC) variations. This study is supported by TUBITAK 114E541 project as a part of the Scientific and Technological Research Projects Funding Program (1001).

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

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

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Temporal and spatial variability of zooplankton on the Faroe shelf in spring 1997-2016

NASA Astrophysics Data System (ADS)

Jacobsen, Sólvá; Gaard, Eilif; Larsen, Karin Margretha Húsgarð; Eliasen, Sólvá Káradóttir; Hátún, Hjálmar

2018-01-01

Zooplankton availability during spring and summer determines the growth and survival of first-feeding fish larvae, and thus impacts the recruitment to both fish prey species and commercial fish stocks. On the Faroe shelf, however, the relative importance of oceanic versus neritic zooplankton species has hitherto not been well understood. In this study, spatio-temporal variability in zooplankton community structure and size spectra on the Faroe shelf is investigated using observations from late April during the period 1997-2016. The main objective was to explore which environmental variables influence the zooplankton community structure in early spring. The zooplankton community in the permanently well mixed central shelf inside the tidal front consists of a mixture of neritic, cosmopolitan and oceanic species. In this region, redundancy analyses showed that chlorophyll concentration had a positive effect on abundance of neritic copepods and meroplankton as well as all zooplankton < 1.2 mm. The abundance variability of these species shows increased production around 2000 and 2008-2009. The highest zooplankton abundance, mainly consisting of Calanus finmarchicus, is however observed off-shore from the tidal front, especially on the western side of the Faroe Plateau. A shift in C. finmarchicus phenology occurred around 2007, resulting in earlier reproduction of this species, and this variability could not be explained by the employed regional environmental parameters. Our results indicate that the Faroe shelf biological production is more dependent on the local primary production and neritic zooplankton species than on the large oceanic C. finmarchicus stock.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

Interannual variability in the magnitude and timing of the spring bloom in the Oyashio region

NASA Astrophysics Data System (ADS)

Okamoto, Suguru; Hirawake, Toru; Saitoh, Sei-Ichi

2010-09-01

Inter-annual variability in the magnitude and timing of the spring bloom was investigated for the Oyashio region (40 °-48 °N, 143 °E-152 °E) using 10 years (from 1998 to 2007) of satellite ocean-color data. Geostrophic currents were examined using satellite altimeter data. Early spring blooms (>1.5 mg m -3) occurred in early April 2001 and late March 2002. The 2001 bloom continued for one month. Late blooms occurred from mid-May 1999, early June 2004 and late April 2006, continuing for about 1 month, 8 days and 16 days, respectively. A strong bloom (4.7 mg m -3) also occurred in mid-April 1998; however, it terminated in early May. We classified the Oyashio region based on the pattern of temporal variation of Chl- a concentr ation from March to June. The spatio-temporal variability in Chl- a concentr ation during spring was different among years. The area where Chl- a concentr ation was highest in April was more extensive in 2001, 2002 and 2006 than usual. In 1999, the area where Chl- a concentr ation was highest in May was the widest among the 10 years. Mesoscale eddies and currents with high velocity were frequently observed in the area of high Chl- a concentr ation east of Hokkaido, propagating Coastal Oyashio Water of low salinity and low density into the oceanic region. That strengthened stratification in the surface layer. We suggest that this seaward transfer of coastal water could be one of the important factors for phytoplankton distribution in two ways: (1) horizontal advection of water with high Chl- a concentr ation and (2) enhancement of stratification in the oceanic region.

Temporal variability in wind-wave climate and its validation with ESSO-NIOT wave atlas for the head Bay of Bengal

NASA Astrophysics Data System (ADS)

Patra, Anindita; Bhaskaran, Prasad K.

2017-08-01

The head Bay region bordering the northern Bay of Bengal is a densely populated area with a complex geomorphologic setting, and highly vulnerable to extreme water levels along with other factors like sea level rise and impact of tropical cyclones. The influence of climate change on wind-wave regime from this region of Bay of Bengal is not known well and that requires special attention, and there is a need to perform its long-term assessment for societal benefits. This study provides a comprehensive analysis on the temporal variability in domain averaged wind speed, significant wave height (SWH) utilizing satellite altimeter data (1992-2012) and mean wave period using ECMWF reanalysis products ERA-Interim (1992-2012) and ERA-20C (1992-2010) over this region. The SWH derived from WAVEWATCH III (WW3) model along with the ERA-Interim reanalysis supplements the observed variability in satellite altimeter observations. Further, the study performs an extensive error estimation of SWH and mean wave period with ESSO-NIOT wave atlas that shows a high degree of under-estimation in the wave atlas mean wave period. Annual mean and wind speed maxima from altimeter show an increasing trend, and to a lesser extent in the SWH. Interestingly, the estimated trend is higher for maxima compared to the mean conditions. Analysis of decadal variability exhibits an increased frequency of higher waves in the present decade compared to the past. Linear trend analysis show significant upswing in spatially averaged ERA-20C mean wave period, whereas the noticed variations are marginal in the ERA-Interim data. A separate trend analysis for the wind-seas, swell wave heights and period from ERA-20C decipher the fact that distant swells governs the local wind-wave climatology over the head Bay region, and over time the swell activity have increased in this region.

Climatic and geologic controls on the piezometry of the Querença-Silves karst aquifer, Algarve (Portugal)

NASA Astrophysics Data System (ADS)

Neves, Maria C.; Costa, Luis; Monteiro, José P.

2016-06-01

Karst aquifers in semi-arid regions, like Querença-Silves (Portugal), are particularly vulnerable to climate variability. For the first time in this region, the temporal structure of a groundwater-level time series (1985-2010) was explored using the continuous wavelet transform. The investigation focused on a set of four piezometers, two at each side of the S. Marcos-Quarteira fault, to demonstrate how each of the two sectors of the aquifer respond to climate-induced patterns. Singular spectral analysis applied to an extended set of piezometers enabled identification of several quasi-periodic modes of variability, with periods of 6.5, 4.3, 3.2 and 2.6 years, which can be explained by low-frequency climate patterns. The geologic forcing accounts for ~15 % of the differential variability between the eastern and western sectors of the aquifer. The western sector displays spatially homogenous piezometric variations, large memory effects and low-pass filtering characteristics, which are consistent with relatively large and uniform values of water storage capacity and transmissivity properties. In this sector, the 6.5-year mode of variability accounts for ~70 % of the total variance of the groundwater levels. The eastern sector shows larger spatial and temporal heterogeneity, is more reactive to short-term variations, and is less influenced by the low-frequency components related to climate patterns.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Understanding Spatial and Temporal Variations of Arctic Circulation Using Oxygen Isotopes of Seawater

NASA Astrophysics Data System (ADS)

Yin, L.; Kopans-Johnson, C. R.; LeGrande, A. N.; Kelly, S.

2015-12-01

The isotopic ratio of 18O to 16O in seawater (2005ppm in ocean water is defined as 𝛿18Oseawater≡0 permil or 0‰) is a fundamental ocean tracer due to its distinct linear relationship with salinity(𝛿18O -S) from regional inland freshwater sources. As opposed to salinity alone, 𝛿18O distinguishes river runoff from sea-ice melt and traces ocean circulation pathways from coastal to open waters and surface to deep waters. Observations from the past 60 years of 𝛿18O seawater were compiled into a database by Schimdt et al. (1999), and subsequently used to calculate a 3-dimensional 1°x1° 𝛿18O global gridded dataset by LeGrande and Schmidt (2006). Although the Schmidt et al. (1999) Global Seawater Oxygen-18 Database (𝛿18Oobs) contains 25,514 measurements used to calculate the global gridded dataset, LeGrande and Schmidt (2006) point out that, "data coverage varies greatly from region to region," with seasonal variability creating biases in areas where sea ice is present. Python Pandas is used to automate the addition of 2,942 records to the Schmidt et al. (1999) Global Seawater Oxygen-18 Database (𝛿18Oobs), and examine the spatial and temporal distributions of 18O in the Arctic Ocean. 10 initial water masses are defined using spatial and temporal trends, clusters of observations, and Arctic surface circulation. Jackknife slope analysis of water mass 𝛿18O -S is used to determine anomalous data points and regional hydrology, resulting in 4 distinct Arctic water masses. These techniques are used to improve the gridded 𝛿18Oseawater dataset by distinguishing unique water masses, and accounting for seasonal variability of complex high latitude areas.

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

NASA Technical Reports Server (NTRS)

McDonald, Kyle; Kimball, John; Zimmermann, Reiner; Way, JoBea; Frolking, Steve; Running, Steve

1999-01-01

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Non-stationary internal tides observed with satellite altimetry

NASA Astrophysics Data System (ADS)

Ray, R. D.; Zaron, E. D.

2011-09-01

Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-1 tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 cm2. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

Non-Stationary Internal Tides Observed with Satellite Altimetry

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Zaron, E. D.

2011-01-01

Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Variations in the Relationship Between Precipitation and Tree Growth in the North-Central Rocky Mountains Identified Using a Tree-Ring Network

NASA Astrophysics Data System (ADS)

Wise, E.

2007-12-01

Much of the western United States is in the midst of a multi-year drought that has placed a renewed sense of urgency on water availability issues. The characterization of variability over relevant space and time scales has emerged as one of the top needs concerning the hydrological cycle, but understanding hydroclimatic variability at decadal and longer time scales has been limited by instrumental data that are both spatially and temporally inadequate. The reconstruction of moisture variables from tree-rings has been recognized as an important source of information on long-term water supply variability. Moisture variables of interest may include annual precipitation, snowpack, summer precipitation, and streamflow. Trees in closely co-located sites can vary widely in the signal they reflect, particularly in a region with the complex topography and hydroclimatic variability that is seen in the north-central Rocky Mountains. In this study, climatic and geospatial information was combined with tree-ring chronologies in order to better-understand factors determining variations in the response of tree growth to a particular precipitation signal. Resulting spatial variability in moisture seasonality and growth response provide insight into the region's moisture patterns and better characterization of the region's hydroclimatic variability.

Ionospheric responses during equinox and solstice periods over Turkey

NASA Astrophysics Data System (ADS)

Karatay, Secil; Cinar, Ali; Arikan, Feza

2017-11-01

Ionospheric electron density is the determining variable for investigation of the spatial and temporal variations in the ionosphere. Total Electron Content (TEC) is the integral of the electron density along a ray path that indicates the total variability through the ionosphere. Global Positioning System (GPS) recordings can be utilized to estimate the TEC, thus GPS proves itself as a useful tool in monitoring the total variability of electron distribution within the ionosphere. This study focuses on the analysis of the variations of ionosphere over Turkey that can be grouped into anomalies during equinox and solstice periods using TEC estimates obtained by a regional GPS network. It is observed that noon time depletions in TEC distributions predominantly occur in winter for minimum Sun Spots Numbers (SSN) in the central regions of Turkey which also exhibit high variability due to midlatitude winter anomaly. TEC values and ionospheric variations at solstice periods demonstrate significant enhancements compared to those at equinox periods.

Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Li, D.

2015-12-01

Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

PubMed

Jin, Changfeng; Jia, Hao; Lanka, Pradyumna; Rangaprakash, D; Li, Lingjiang; Liu, Tianming; Hu, Xiaoping; Deshpande, Gopikrishna

2017-09-01

Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. Specifically, we test whether PTSD is characterized by elevated static connectivity, coupled with decreased temporal variability of those connections, with the latter providing greater sensitivity toward the pathology than the former. Static functional connectivity (FC; nondirectional zero-lag correlation) and static effective connectivity (EC; directional time-lagged relationships) were obtained over the entire brain using conventional models. Dynamic FC and dynamic EC were estimated by letting the conventional models to vary as a function of time. Statistical separation and discriminability of these metrics between the groups and their ability to accurately predict the diagnostic label of a novel subject were ascertained using separate support vector machine classifiers. Our findings support our hypothesis that PTSD subjects have stronger static connectivity, but reduced temporal variability of connectivity. Further, machine learning classification accuracy obtained with dynamic FC and dynamic EC was significantly higher than that obtained with static FC and static EC, respectively. Furthermore, results also indicate that the ease with which brain regions engage or disengage with other regions may be more sensitive to underlying pathology than the strength with which they are engaged. Future studies must examine whether this is true only in the case of PTSD or is a general organizing principle in the human brain. Hum Brain Mapp 38:4479-4496, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

Boreal spring precipitation variability in the cold arid western Himalaya during the last millennium, regional linkages, and socio-economic implications

NASA Astrophysics Data System (ADS)

Yadava, Akhilesh K.; Bräuning, Achim; Singh, Jayendra; Yadav, Ram R.

2016-07-01

Precipitation in the monsoon shadow zone of the western Himalayan region, largely under the influence of mid-latitude westerlies, is the dominant regional socioeconomic driver. Current knowledge of long-term regional precipitation variability is scarce due to spatially and temporally limited weather and high-resolution proxy climate records. We developed the first boreal spring precipitation reconstruction for the western Himalaya covering the last millennium (1030-2011 C.E.). The annually resolved reconstruction is based on a large tree-ring data set of Himalayan cedar (Cedrus deodara) and neoza pine (Pinus gerardiana) from 16 ecologically homogeneous moisture stressed settings in Kinnaur, western Indian Himalaya. The precipitation reconstruction revealed persistent long-term spring droughts from the 12th to early 16th century C.E. and pluvial from the late 16th century C.E. to recent decades. The late 15th and early 16th centuries (1490-1514 C.E.) displayed the driest episode, with precipitation being ∼15% lower than the long-term mean. The early 19th century (1820-1844 C.E.) was the wettest period of the past millennium, with mean precipitation ∼13% above the long-term mean. The reconstructed boreal spring precipitation from the western Himalaya revealed large-scale consistency with hydrological records from westerly dominated regions in Central Asia, indicating synoptic-scale changes in atmospheric circulation during the major part of the Medieval and Little Ice Age periods. Protracted droughts in Central Asia could have caused severe contraction of the regional economy, as indicated by striking coherence of reconstructed drought periods and historic social upheavals and invasions of India from Central and Western Asian invaders. Vulnerability to climatic extremes underpins the need to develop a better understanding of the temporal and spatial variability in regional hydroclimate in order to devise viable water resource management plans.

Temporal variability of exchange between groundwater and surface water based on high-frequency direct measurements of seepage at the sediment-water interface

USGS Publications Warehouse

Rosenberry, Donald O.; Sheibley, Rich W.; Cox, Stephen E.; Simonds, Frederic W.; Naftz, David L.

2013-01-01

Seepage at the sediment-water interface in several lakes, a large river, and an estuary exhibits substantial temporal variability when measured with temporal resolution of 1 min or less. Already substantial seepage rates changed by 7% and 16% in response to relatively small rain events at two lakes in the northeastern USA, but did not change in response to two larger rain events at a lake in Minnesota. However, seepage at that same Minnesota lake changed by 10% each day in response to withdrawals from evapotranspiration. Seepage increased by more than an order of magnitude when a seiche occurred in the Great Salt Lake, Utah. Near the head of a fjord in Puget Sound, Washington, seepage in the intertidal zone varied greatly from −115 to +217 cm d−1 in response to advancing and retreating tides when the time-averaged seepage was upward at +43 cm d−1. At all locations, seepage variability increased by one to several orders of magnitude in response to wind and associated waves. Net seepage remained unchanged by wind unless wind also induced a lake seiche. These examples from sites distributed across a broad geographic region indicate that temporal variability in seepage in response to common hydrological events is much larger than previously realized. At most locations, seepage responded within minutes to changes in surface-water stage and within minutes to hours to groundwater recharge associated with rainfall. Likely implications of this dynamism include effects on water residence time, geochemical transformations, and ecological conditions at and near the sediment-water interface.

Dynamical Downscaling over Siberia: Is there an added value in representing recent climate conditions?

NASA Astrophysics Data System (ADS)

Klehmet, K.; Rockel, B.

2012-04-01

The analysis of long-term changes and variability of climate variables for the large areal extent of Siberia - covering arctic, subarctic and temperate northern latitudes - is hampered by the sparseness of in-situ observations. To counteract this deficiency we aimed to provide a reconstruction of regional climate for the period 1948-2010 getting homogenous, consistent fields of various terrestrial and atmospheric parameters for Siberia. In order to obtain in addition a higher temporal and spatial resolution than global datasets can provide, we performed the reconstruction using the regional climate model COSMO-CLM (climate mode of the limited area model COSMO developed by the German weather service). However, the question arises whether the dynamically downscaled data of reanalysis can improve the representation of recent climate conditions. As global forcing for the initialization and the regional boundaries we use NCEP-1 Reanalysis of the National Centers for Environmental Prediction since it has the longest temporal data coverage among the reanalysis products. Additionally, spectral nudging is applied to prevent the regional model from deviating from the prescribed large-scale circulation within the whole simulation domain. The area of interest covers a region in Siberia, spanning from the Laptev Sea and Kara Sea to Northern Mongolia and from the West Siberian Lowland to the border of Sea of Okhotsk. The current horizontal resolution is of about 50 km which is planned to be increased to 25 km. To answer the question, we investigate spatial and temporal characteristics of temperature and precipitation of the model output in comparison to global reanalysis data (NCEP-1, ERA40, ERA-Interim). As reference Russian station data from the "Global Summary of the Day" data set, provided by NCDC, is used. Temperature is analyzed with respect to its climatologically spatial patterns across the model domain and its variability of extremes based on climate indices derived from daily mean, maximum, minimum temperature (e.g. frost days) for different subregions. The decreasing number of frost days from north to south of the region, calculated from the reanalysis datasets and COSMO-CLM output, indicates the temperature gradient from the arctic to temperate latitudes. For most of the considered subregions NCEP-1 shows more frost days than ERA-Interim and COSMO-CLM.

Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Cognitive and Anatomical Underpinnings of the Conceptual Knowledge for Common Objects and Familiar People: A Repetitive Transcranial Magnetic Stimulation Study

PubMed Central

Campanella, Fabio; Fabbro, Franco; Urgesi, Cosimo

2013-01-01

Several studies have addressed the issue of how knowledge of common objects is organized in the brain, whereas the cognitive and anatomical underpinnings of familiar people knowledge have been less explored. Here we applied repetitive transcranial magnetic stimulation (rTMS) over the left and right temporal poles before asking healthy individuals to perform a speeded word-to-picture matching task using familiar people and common objects as stimuli. We manipulated two widely used semantic variables, namely the semantic distance and the familiarity of stimuli, to assess whether the semantic organization of familiar people knowledge is similar to that of common objects. For both objects and faces we reliably found semantic distance and familiarity effects, with less accurate and slower responses for stimulus pairs that were more closely related and less familiar. However, the effects of semantic variables differed across categories, with semantic distance effects larger for objects and familiarity effects larger for faces, suggesting that objects and faces might share a partially comparable organization of their semantic representations. The application of rTMS to the left temporal pole modulated, for both categories, semantic distance, but not familiarity effects, revealing that accessing object and face concepts might rely on overlapping processes within left anterior temporal regions. Crucially, rTMS of the left temporal pole affected only the recognition of pairs of stimuli that could be discriminated at specific levels of categorization (e.g., two kitchen tools or two famous persons), with no effect for discriminations at either superordinate or individual levels. Conversely, rTMS of the right temporal pole induced an overall slowing of reaction times that positively correlated with the visual similarity of the stimuli, suggesting a more perceptual rather than semantic role of the right anterior temporal regions. Results are discussed in the light of current models of face and object semantic representations in the brain. PMID:23704999

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder.

PubMed

Demirtaş, Murat; Tornador, Cristian; Falcón, Carles; López-Solà, Marina; Hernández-Ribas, Rosa; Pujol, Jesús; Menchón, José M; Ritter, Petra; Cardoner, Narcis; Soriano-Mas, Carles; Deco, Gustavo

2016-08-01

Resting-state fMRI (RS-fMRI) has become a useful tool to investigate the connectivity structure of mental health disorders. In the case of major depressive disorder (MDD), recent studies regarding the RS-fMRI have found abnormal connectivity in several regions of the brain, particularly in the default mode network (DMN). Thus, the relevance of the DMN to self-referential thoughts and ruminations has made the use of the resting-state approach particularly important for MDD. The majority of such research has relied on the grand averaged functional connectivity measures based on the temporal correlations between the BOLD time series of various brain regions. We, in our study, investigated the variations in the functional connectivity over time at global and local level using RS-fMRI BOLD time series of 27 MDD patients and 27 healthy control subjects. We found that global synchronization and temporal stability were significantly increased in the MDD patients. Furthermore, the participants with MDD showed significantly increased overall average (static) functional connectivity (sFC) but decreased variability of functional connectivity (vFC) within specific networks. Static FC increased to predominance among the regions pertaining to the default mode network (DMN), while the decreased variability of FC was observed in the connections between the DMN and the frontoparietal network. Hum Brain Mapp 37:2918-2930, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Complementary Roles for Amygdala and Periaqueductal Gray in Temporal-Difference Fear Learning

ERIC Educational Resources Information Center

Cole, Sindy; McNally, Gavan P.

2009-01-01

Pavlovian fear conditioning is not a unitary process. At the neurobiological level multiple brain regions and neurotransmitters contribute to fear learning. At the behavioral level many variables contribute to fear learning including the physical salience of the events being learned about, the direction and magnitude of predictive error, and the…

Evapotranspiration in winter wheat under different grazing and tillage practices in the southern Great Plains

USDA-ARS?s Scientific Manuscript database

Precipitation in the Southern Great Plains (SGP) is highly variable both spatially and temporally with recurring periods of severe drought. Winter wheat (Triticum aestivum L.) – summer fallow system with conventional tillage is the principal dryland cropping system in this region for both grazing an...

Spatial And Temporal Variability Of Wildland Fire Emissions Over The U.S.

Treesearch

Yongqiang Liu

2003-01-01

Wildland fires release large amounts of particulate matter (PM), CO, S02, NOx,, and Volatile Organic Carbon (VOC), which can cause serious consequence of regional and local air quality (Sandberg et al., 1999). All these components except VOC are the principal pollutants whose emissions are subject to the National Ambient...

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

USGS Publications Warehouse

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

2015-01-01

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

Temporal Dynamics and Persistence of Spatial Patterns: from Groundwater to Soil Moisture to Transpiration

NASA Astrophysics Data System (ADS)

Blume, T.; Hassler, S. K.; Weiler, M.

2017-12-01

Hydrological science still struggles with the fact that while we wish for spatially continuous images or movies of state variables and fluxes at the landscape scale, most of our direct measurements are point measurements. To date regional measurements resolving landscape scale patterns can only be obtained by remote sensing methods, with the common drawback that they remain near the earth surface and that temporal resolution is generally low. However, distributed monitoring networks at the landscape scale provide the opportunity for detailed and time-continuous pattern exploration. Even though measurements are spatially discontinuous, the large number of sampling points and experimental setups specifically designed for the purpose of landscape pattern investigation open up new avenues of regional hydrological analyses. The CAOS hydrological observatory in Luxembourg offers a unique setup to investigate questions of temporal stability, pattern evolution and persistence of certain states. The experimental setup consists of 45 sensor clusters. These sensor clusters cover three different geologies, two land use classes, five different landscape positions, and contrasting aspects. At each of these sensor clusters three soil moisture/soil temperature profiles, basic climate variables, sapflow, shallow groundwater, and stream water levels were measured continuously for the past 4 years. We will focus on characteristic landscape patterns of various hydrological state variables and fluxes, studying their temporal stability on the one hand and the dependence of patterns on hydrological states on the other hand (e.g. wet vs dry). This is extended to time-continuous pattern analysis based on time series of spatial rank correlation coefficients. Analyses focus on the absolute values of soil moisture, soil temperature, groundwater levels and sapflow, but also investigate the spatial pattern of the daily changes of these variables. The analysis aims at identifying hydrologic signatures of the processes or landscape characteristics acting as major controls. While groundwater, soil water and transpiration are closely linked by the water cycle, they are controlled by different processes and we expect this to be reflected in interlinked but not necessarily congruent patterns and responses.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

High Resolution Studies of the Structure of the Solar Atmosphere

DTIC Science & Technology

1993-08-04

two-fluid solar wind model", submitted to J. Geophys. Res., August 1993. M. B. Arndt, S. R. Habbal, and M. Karovska , "Discrete and localized nature of...the variable emission from active regions", submitted to Solar Phys., August 1993. M. Karovska and F. Blundell, "The fine structure at the limb in a...coronal hole", submitted to Ap. J, August 1993. M. Karovska , M. Arndt and S. R. Habbal, "Spatial and temporal variability of the emission at the limb

Long-term patterns of air temperatures, daily temperature range, precipitation, grass-reference evapotranspiration and aridity index in the USA great plains: Part II. Temporal trends

NASA Astrophysics Data System (ADS)

Kukal, M.; Irmak, S.

2016-11-01

Detection of long-term changes in climate variables over large spatial scales is a very important prerequisite to the development of effective mitigation and adaptation measures for the future potential climate change and for developing strategies for future hydrologic balance analyses under changing climate. Moreover, there is a need for effective approaches of providing information about these changes to decision makers, water managers and stakeholders to aid in efficient implementation of the developed strategies. This study involves computation, mapping and analyses of long-term (1968-2013) county-specific trends in annual, growing-season (1st May-30th September) and monthly air temperatures [(maximum (Tmax), minimum (Tmin) and average (Tavg)], daily temperature range (DTR), precipitation, grass reference evapotranspiration (ETo) and aridity index (AI) over the USA Great Plains region using datasets from over 800 weather station sites. Positive trends in annual Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were observed in 71%, 89%, 85%, 31%, 61%, 38% and 66% of the counties in the region, respectively, whereas these proportions were 48%, 89%, 62%, 20%, 57%, 28%, and 63%, respectively, for the growing-season averages of the same variables. On a regional average basis, the positive trends in growing-season Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were 0.18 °C decade-1, 0.19 °C decade-1, 0.17 °C decade-1, 0.09 °C decade-1, 1.12 mm yr-1, 0.4 mm yr-1 and 0.02 decade-1, respectively, and the negative trends were 0.21 °C decade-1, 0.06 °C decade-1, 0.09 °C decade-1, 0.22 °C decade-1, 1.16 mm yr-1, 0.76 mm yr-1 and 0.02 decade-1, respectively. The temporal trends were highly variable in space and were appropriately represented using monthly, annual and growing-season maps developed using Geographic Information System (GIS) techniques. The long-term and spatial and temporal information and data for a large region provided in this study can be used to analyze county-level trends in important climatic/hydrologic variables in context of climate change, water resources, agricultural and natural resources response to climate change.

Temporal and spatial variation in pharmaceutical concentrations in an urban river system

USGS Publications Warehouse

Burns, Emily E.; Carter, Laura J.; Kolpin, Dana W.; Thomas-Oates, Jane; Boxall, Alistair B.A.

2018-01-01

Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse.

Anatomy is strategy: Skilled reading differences associated with structural connectivity differences in the reading network

PubMed Central

Graves, William W.; Binder, Jeffrey R.; Desai, Rutvik H.; Humphries, Colin; Stengel, Benjamin C.; Seidenberg, Mark S.

2014-01-01

Are there multiple ways to be a skilled reader? To address this longstanding, unresolved question, we hypothesized that individual variability in using semantic information in reading aloud would be associated with neuroanatomical variation in pathways linking semantics and phonology. Left-hemisphere regions of interest for diffusion tensor imaging analysis were defined based on fMRI results, including two regions linked with semantic processing – angular gyrus (AG) and inferior temporal sulcus (ITS) – and two linked with phonological processing – posterior superior temporal gyrus (pSTG) and posterior middle temporal gyrus (pMTG). Effects of imageability (a semantic measure) on response times varied widely among individuals and covaried with the volume of pathways through the ITS and pMTG, and through AG and pSTG, partially overlapping the inferior longitudinal fasciculus and the posterior branch of the arcuate fasciculus. These results suggest strategy differences among skilled readers associated with structural variation in the neural reading network. PMID:24735993

Spatio-temporal activity of lightnings over Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Matsangouras, I. T.; Chronis, T. G.

2012-04-01

Extreme precipitation events are always associated with convective weather conditions driving to intense lightning activity: Cloud to Ground (CG), Ground to Cloud (GC) and Cloud to Cloud (CC). Thus, the study of lightnings, which typically occur during thunderstorms, gives evidence of the spatio-temporal variability of intense precipitation. Lightning is a natural phenomenon in the atmosphere, being a major cause of storm related with deaths and main trigger of forest fires during dry season. Lightning affects the many electrochemical systems of the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. An operational lightning detection network (LDN) has been established since 2007 by HNMS, consisting of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. In this study, the spatial and temporal variability of recorded lightnings (CG, GC and CC) are analyzed over Greece, during the period from January 14, 2008 to December 31, 2009, for the first time. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS). In addition to the analysis of spatio-temporal activity over Greece, the HNMS-LDN characteristics are also presented. The results of the performed analysis reveal the specific geographical sub-regions associated with lightnings incidence. Lightning activity occurs mainly during the autumn season, followed by summer and spring. Higher frequencies of flashes appear over Ionian and Aegean Sea than over land during winter period against continental mountainous regions during summer period.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Water clarity in the Florida Keys, USA, as observed from space (1984-2002)

NASA Astrophysics Data System (ADS)

Palandro, D. A.; Hu, C.; Andrefouet, S.; Muller-Karger, F. E.; Hallock, P.

2007-12-01

Landsat TM and ETM+ satellite data were used to derive the diffuse attenuation coefficient (Kd, m-1), a measure of water clarity, for 29 sites throughout the Florida Keys Reef Tract. A total of 28 individual Landsat images between 1984 and 2002 were used, with imagery gathered every two years for spring seasons and every six years for fall seasons. Useful information was obtained by Landsat bands 1 (blue) and 2 (green), except when sites were covered by clouds or showed turbid water. Landsat band 3 (red) provided no consistent data due to the high absorption of red light by water. Because image sampling represented only one or two samples per year on specific days, and because water turbidity may change over short time scales, it was not possible to assess temporal trends at the sites with the Landsat data. Kd values in band 1 were higher in the spring (mean spring = 0.034 m-1, mean fall = 0.031 m-1) and band 2 were higher in the fall (mean spring = 0.056 m-1, mean fall = 0.058 m-1), but the differences were not statistically significant. Spatial variability was high between sites and between regions (Upper, Middle and Lower Keys), with band 1 ranges of 0.019 m-1 - 0.060 m-1 and band 2 ranges of 0.036 m-1 - 0.076 m-1. The highest Kd values were found in the Upper Keys, followed by the Middle Keys and Lower Keys, respectively. This result must be taken in context however, two Middle Keys sites were found to be inconsistent due to high turbidity, obscuring the benthos and altering our assumption of a visible seafloor, which the algorithm is dependent upon. If all Middle Keys data were valid it is likely that this region would have the highest Kd values for both bands. The Landsat-derived Kd values, and inherent variability, may be influenced by the dominant water mass associated with each Florida Keys region, as well as localized oceanic variables. The methodology used here may be applied to other reef areas and used with satellites that offer higher temporal resolution to assess temporal change and variability.

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

The advantages, and challenges, in using multiple techniques in the estimation of surface water-groundwater fluxes.

NASA Astrophysics Data System (ADS)

Shanafield, M.; Cook, P. G.

2014-12-01

When estimating surface water-groundwater fluxes, the use of complimentary techniques helps to fill in uncertainties in any individual method, and to potentially gain a better understanding of spatial and temporal variability in a system. It can also be a way of preventing the loss of data during infrequent and unpredictable flow events. For example, much of arid Australia relies on groundwater, which is recharged by streamflow through ephemeral streams during flood events. Three recent surface water/groundwater investigations from arid Australian systems provide good examples of how using multiple field and analysis techniques can help to more fully characterize surface water-groundwater fluxes, but can also result in conflicting values over varying spatial and temporal scales. In the Pilbara region of Western Australia, combining streambed radon measurements, vertical heat transport modeling, and a tracer test helped constrain very low streambed residence times, which are on the order of minutes. Spatial and temporal variability between the methods yielded hyporheic exchange estimates between 10-4 m2 s-1 and 4.2 x 10-2 m2 s-1. In South Australia, three-dimensional heat transport modeling captured heterogeneity within 20 square meters of streambed, identifying areas of sandy soil (flux rates of up to 3 m d-1) and clay (flux rates too slow to be accurately characterized). Streamflow front modeling showed similar flux rates, but averaged over 100 m long stream segments for a 1.6 km reach. Finally, in central Australia, several methods are used to decipher whether any of the flow down a highly ephemeral river contributes to regional groundwater recharge, showing that evaporation and evapotranspiration likely accounts for all of the infiltration into the perched aquifer. Lessons learned from these examples demonstrate the influences of the spatial and temporal variability between techniques on estimated fluxes.

Characterization of the Fire Regime and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2016-12-01

The Upper Guinean forest (UGF), encompassing the tropical regions of West Africa, is a globally significant biodiversity hotspot and a critically important socio-economic and ecological resource for the region. However, the UGF is one of the most human-disturbed tropical forest ecosystems with the only remaining large patches of original forests distributed in protected areas, which are embedded in a hotspot of climate stress & land use pressures, increasing their vulnerability to fire. We hypothesized that human impacts and climate interact to drive spatial and temporal variability in fire, with fire exhibiting distinctive seasonality and sensitivity to drought in areas characterized by different population densities, agricultural practices, vegetation types, and levels of forest degradation. We used the MODIS active fire product to identify and characterize fire activity in the major ecoregions of the UGF. We used TRMM rainfall data to measure climatic variability and derived indicators of human land use from a variety of geospatial datasets. We employed time series modeling to identify the influences of drought indices and other antecedent climatic indicators on temporal patterns of active fire occurrence. We used a variety of modeling approaches to assess the influences of human activities and land cover variables on the spatial pattern of fire activity. Our results showed that temporal patterns of fire activity in the UGF were related to precipitation, but these relationships were spatially heterogeneous. The pattern of fire seasonality varied geographically, reflecting both climatological patterns and agricultural practices. The spatial pattern of fire activity was strongly associated with vegetation gradients and anthropogenic activities occurring at fine spatial scales. The Guinean forest-savanna mosaic ecoregion had the most fires. This study contributes to our understanding of UGF fire regime and the spatio-temporal dynamics of tropical forest fires in response to intense human and climatic drivers.

Periodic and Aperiodic Variability in the Molecular Cloud ρ Ophiuchus

NASA Astrophysics Data System (ADS)

Parks, J. Robert; Plavchan, Peter; White, Russel J.; Gee, Alan H.

2014-03-01

Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and Ks -band photometric measurements with a cadence of ~1 day are obtained over three observing seasons spanning ~2.5 yr it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔKs -band amplitudes from 0.044 to 2.31 mag and Δ(J - Ks ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the Ks time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic "eclipse-like" features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism could be identified for these variable stars.

Rainfall Climatology over Asir Region, Saudi Arabia

NASA Astrophysics Data System (ADS)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Heat wave phenomenon in southern Slovakia: long-term changes and variability of daily maximum air temperature in Hurbanovo within the 1901-2009 period

NASA Astrophysics Data System (ADS)

Pecho, J.; Výberči, D.; Jarošová, M.; Å¥Astný, P. Å.

2010-09-01

Analysis of long-term changes and temporal variability of heat waves incidence in the region of southern Slovakia within the 1901-2009 periods is a goal of the presented contribution. It is expected that climate change in terms of global warming would amplify temporal frequency and spatial extension of extreme heat wave incidence in region of central Europe in the next few decades. The frequency of occurrence and amplitude of heat waves may be impacted by changes in the temperature regime. Heat waves can cause severe thermal environmental stress leading to higher hospital admission rates, health complications, and increased mortality. These effects arise because of one or more meteorology-related factors such as higher effective temperatures, sunshine, more consecutive hot days and nights, stagnation, increased humidity, increased pollutant emissions, and accelerated photochemical smog and particulate formation. Heat waves bring about higher temperatures, increased solar heating of buildings, inhibited ventilation, and a larger number of consecutive warm days and nights. All of these effects increase the thermal loads on buildings, reduce their ability to cool down, and increase indoor temperatures. The paper is focused to analysis of long-term and inter-decadal temporal variability of heat waves occurrence at meteorological station Hurbanovo (time-series of daily maximum air temperature available from at least 1901). We can characterize the heat waves by its magnitude and duration, hence both of these characteristics need to be investigated together using sophisticated statistical methods developed particularly for the analysis of extreme hydrological events. We investigated particular heat wave periods either from the severity point of view using HWI index. In the paper we also present the results of statistical analysis of daily maximum air temperature within 1901-2009 period. Apart from these investigation efforts we also focused on synoptic causes of heat wave incidence in connection with macro scale circulation patterns in central European region.

Quantifying interindividual variability and asymmetry of face-selective regions: a probabilistic functional atlas.

PubMed

Zhen, Zonglei; Yang, Zetian; Huang, Lijie; Kong, Xiang-Zhen; Wang, Xu; Dang, Xiaobin; Huang, Yangyue; Song, Yiying; Liu, Jia

2015-06-01

Face-selective regions (FSRs) are among the most widely studied functional regions in the human brain. However, individual variability of the FSRs has not been well quantified. Here we use functional magnetic resonance imaging (fMRI) to localize the FSRs and quantify their spatial and functional variabilities in 202 healthy adults. The occipital face area (OFA), posterior and anterior fusiform face areas (pFFA and aFFA), posterior continuation of the superior temporal sulcus (pcSTS), and posterior and anterior STS (pSTS and aSTS) were delineated for each individual with a semi-automated procedure. A probabilistic atlas was constructed to characterize their interindividual variability, revealing that the FSRs were highly variable in location and extent across subjects. The variability of FSRs was further quantified on both functional (i.e., face selectivity) and spatial (i.e., volume, location of peak activation, and anatomical location) features. Considerable interindividual variability and rightward asymmetry were found in all FSRs on these features. Taken together, our work presents the first effort to characterize comprehensively the variability of FSRs in a large sample of healthy subjects, and invites future work on the origin of the variability and its relation to individual differences in behavioral performance. Moreover, the probabilistic functional atlas will provide an adequate spatial reference for mapping the face network. Copyright © 2015 Elsevier Inc. All rights reserved.

Temporally Adaptive Sampling: A Case Study in Rare Species Survey Design with Marbled Salamanders (Ambystoma opacum)

PubMed Central

Charney, Noah D.; Kubel, Jacob E.; Eiseman, Charles S.

2015-01-01

Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds. PMID:25799224

Coronal energy distribution and X-ray activity in the small scale magnetic field of the quiet sun

NASA Technical Reports Server (NTRS)

Habbal, S. R.

1992-01-01

The energy distribution in the small-scale magnetic field that pervades the solar surface, and its relationship to X-ray/coronal activity are discussed. The observed emission from the small scale structures, at temperatures characteristic of the chromosphere, transition region and corona, emanates from the boundaries of supergranular cells, within coronal bright points. This emission is characterized by a strong temporal and spatial variability with no definite pattern. The analysis of simultaneous, multiwavelength EUV observations shows that the spatial density of the enhanced as well as variable emission from the small scale structures exhibits a pronounced temperature dependence with significant maxima at 100,000 and 1,000,000 K. Within the limits of the spatial (1-5 arcsec) and temporal (1-5 min) resolution of data available at present, the observed variability in the small scale structure cannot account for the coroal heating of the quiet sun. The characteristics of their emission are more likely to be an indicator of the coronal heating mechanisms.

Paleoclimate reconstruction along the Pole-Equator-Pole transect of the Americas (PEP 1)

USGS Publications Warehouse

Markgraf, Vera; Baumgartner, T.R.; Bradbury, J.P.; Diaz, Henry F.; Dunbar, R.B.; Luckman, B.H.; Seltzer, G.O.; Swetnam, T.W.; Villalba, R.

2000-01-01

Examples are presented of inter-hemispheric comparison of instrumental climate and paleoclimate proxy records from the Americas for different temporal scales. Despite a certain symmetry of seasonal precipitation patterns along the PEP I transect, decadal variability of winter precipitation shows different characteristics in terms of amplitude and frequency in both the last 100 and last 1000 years. Such differences in variability are also seen in a comparison of time series of different El Nino/Southern Oscillation proxy records from North and South America, however, these differences do not appear to affect the spatial correlation with Pacific sea surface temperature patterns. Local and regional differences in response to climate change are even more pronounced for records with lower temporal resolution, and inter-hemispheric synchroneity may or may not be indicative of the same forcing. This aspect is illustrated in an inter-hemispheric comparison of the last 1000 years of glacier variability, and of the full- and lateglacial lake level history.

Seasonal Predictability in a Model Atmosphere.

NASA Astrophysics Data System (ADS)

Lin, Hai

2001-07-01

The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

Assessing the Change in Rainfall Characteristics and Trends for the Southern African ITCZ Region

NASA Astrophysics Data System (ADS)

Baumberg, Verena; Weber, Torsten; Helmschrot, Jörg

2015-04-01

Southern Africa is strongly influenced by the movement and intensity of the Intertropical Convergence Zone (ITCZ) thus determining the climate in this region with distinct seasonal and inter-annual rainfall dynamics. The amount and variability of rainfall affect the various ecosystems by controlling the hydrological system, regulating water availability and determining agricultural practices. Changes in rainfall characteristics potentially caused by climate change are of uppermost relevance for both ecosystem functioning and human well-being in this region and, thus, need to be investigated. To analyse the rainfall variability governed by the ITCZ in southern Africa, observational daily rainfall datasets with a high spatial resolution of 0.25° x 0.25° (about 28 km x 28 km) from satellite-based Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS) are used. These datasets extend from 1998 to 2008 and 1948 to 2010, respectively, and allow for the assessment of rainfall characteristics over different spatial and temporal scales. Furthermore, a comparison of TRMM and GLDAS and, where available, with observed data will be made to determine the differences of both datasets. In order to quantify the intra- and inner-annual variability of rainfall, the amount of total rainfall, duration of rainy seasons and number of dry spells along with further indices are calculated from the observational datasets. Over the southern African ITCZ region, the rainfall characteristics change moving from wetter north to the drier south, but also from west to east, i.e. the coast to the interior. To address expected spatial and temporal variabilities, the assessment of changes in the rainfall parameters will be carried out for different transects in zonal and meridional directions over the region affected by the ITCZ. Revealing trends over more than 60 years, the results will help to identify and understand potential impacts of climate change on rainfall characteristics for the southern African ITCZ region. The findings of this study will feed into various ecosystem assessment and biodiversity change studies in Angola and Zambia.

City scale pollen concentration variability

NASA Astrophysics Data System (ADS)

van der Molen, Michiel; van Vliet, Arnold; Krol, Maarten

2016-04-01

Pollen are emitted in the atmosphere both in the country-side and in cities. Yet the majority of the population is exposed to pollen in cities. Allergic reactions may be induced by short-term exposure to pollen. This raises the question how variable pollen concentration in cities are in temporally and spatially, and how much of the pollen in cities are actually produced in the urban region itself. We built a high resolution (1 × 1 km) pollen dispersion model based on WRF-Chem to study a city's pollen budget and the spatial and temporal variability in concentration. It shows that the concentrations are highly variable, as a result of source distribution, wind direction and boundary layer mixing, as well as the release rate as a function of temperature, turbulence intensity and humidity. Hay Fever Forecasts based on such high resolution emission and physical dispersion modelling surpass traditional hay fever warning methods based on temperature sum methods. The model gives new insights in concentration variability, personal and community level exposure and prevention. The model will be developped into a new forecast tool to serve allergic people to minimize their exposure and reduce nuisance, coast of medication and sick leave. This is an innovative approach in hay fever warning systems.

Black Sea spectral bio-optical models based on satellite data and their applications for assessment of spatial and temporal variability in waters transparency, chlorophyll a content and primary production

NASA Astrophysics Data System (ADS)

Churilova, T.; Suslin, V.

2012-04-01

Satellite observations of ocean color provide a unique opportunity in oceanography to assess productivity of the sea on different spatial and temporal scales. However it has been shown that the standard SeaWiFS algorithm generally overestimates summer chlorophyll concentration and underestimates pigment content during spring phytoplankton bloom in comparison with in situ measurements. It is required to develop regional algorithms which are based on biooptical characteristics typical for the Sea and consequently could be used for correct transformation of spectral features of water-leaving radiance to chlorophyll a concentrations (Chl), light absorption features of suspended and dissolved organic matter (CDM), downwelling light attenuation coefficient/euphotic zone depth (PAR1%) and rate of primary synthesis of organic substances (PP). The numerous measurements of light absorption spectra of phytoplankton, non-algal particles and coloured dissolved organic matter carried out since 1996 in different seasons and regions of the Black Sea allowed to make a parameterization of the light absorption by all optically active components. Taking into account regional peculiarities of the biooptical parameters, their difference between seasons, shallow and deep-waters, their depth-dependent variability within photosynthetic zone regional spectral models for estimation of chlorophyll a concentration (Chl Model), colored dissolved and suspended organic matter absorption (CDM Model), downwelling irradiance (PAR Model) and primary production (PP Model) have been developed based on satellite data. Test of validation of models showed appropriate accuracy of the models. The developed models have been applied for estimation of spatial/temporal variability of chlorophyll a, dissolved organic matter concentrations, waters transparency, euphotic zone depth and primary production based on SeaWiFS data. Two weeks averaged maps of spatial distribution of these parameters have been composed for period from 1998 to 2009 (most of them presented on site http://blackseacolor.com/browser3.html). Comparative analysis of long-term series (since 1998) of these parameters with subsurface water temperature (SST) and solar radiance of the sea surface (PAR-0m) revealed the key factors determining the seasonal and inter-annual variations of Chl, PAR1%, CDM, PP. The seasonal dynamics of these parameters were more pronounced compared with inter-annual variability. The later was related to climate effect. In deep-waters region relatively lower SST during cold winters were forcing more intensive winter-spring phytoplankton bloom. In north-western shelf inter-annual variability in river (Danube) run off, which was related to climate change as well, determined year-to-year changing in Chl, CDM, PAR1%, and PP.

Increased Expression of Brain-Derived Neurotrophic Factor Transcripts I and VI, cAMP Response Element Binding, and Glucocorticoid Receptor in the Cortex of Patients with Temporal Lobe Epilepsy.

PubMed

Martínez-Levy, G A; Rocha, L; Rodríguez-Pineda, F; Alonso-Vanegas, M A; Nani, A; Buentello-García, R M; Briones-Velasco, M; San-Juan, D; Cienfuegos, J; Cruz-Fuentes, C S

2018-05-01

A body of evidence supports a relevant role of brain-derived neurotrophic factor (BDNF) in temporal lobe epilepsy (TLE). Magnetic resonance data reveal that the cerebral atrophy extends to regions that are functionally and anatomically connected with the hippocampus, especially the temporal cortex. We previously reported an increased expression of BDNF messenger for the exon VI in the hippocampus of temporal lobe epilepsy patients compared to an autopsy control group. Altered levels of this particular transcript were also associated with pre-surgical use of certain psychotropic. We extended here our analysis of transcripts I, II, IV, and VI to the temporal cortex since this cerebral region holds intrinsic communication with the hippocampus and is structurally affected in patients with TLE. We also assayed the cyclic adenosine monophosphate response element-binding (CREB) and glucocorticoid receptor (GR) genes as there is experimental evidence of changes in their expression associated with BDNF and epilepsy. TLE and pre-surgical pharmacological treatment were considered as the primary clinical independent variables. Transcripts BDNF I and BDNF VI increased in the temporal cortex of patients with pharmacoresistant TLE. The expression of CREB and GR expression follow the same direction. Pre-surgical use of selective serotonin reuptake inhibitors, carbamazepine (CBZ) and valproate (VPA), was associated with the differential expression of specific BDNF transcripts and CREB and GR genes. These changes could have functional implication in the plasticity mechanisms related to temporal lobe epilepsy.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Words in Context: The Effects of Length, Frequency, and Predictability on Brain Responses During Natural Reading

PubMed Central

Schuster, Sarah; Hawelka, Stefan; Hutzler, Florian; Kronbichler, Martin; Richlan, Fabio

2016-01-01

Word length, frequency, and predictability count among the most influential variables during reading. Their effects are well-documented in eye movement studies, but pertinent evidence from neuroimaging primarily stem from single-word presentations. We investigated the effects of these variables during reading of whole sentences with simultaneous eye-tracking and functional magnetic resonance imaging (fixation-related fMRI). Increasing word length was associated with increasing activation in occipital areas linked to visual analysis. Additionally, length elicited a U-shaped modulation (i.e., least activation for medium-length words) within a brain stem region presumably linked to eye movement control. These effects, however, were diminished when accounting for multiple fixation cases. Increasing frequency was associated with decreasing activation within left inferior frontal, superior parietal, and occipito-temporal regions. The function of the latter region—hosting the putative visual word form area—was originally considered as limited to sublexical processing. An exploratory analysis revealed that increasing predictability was associated with decreasing activation within middle temporal and inferior frontal regions previously implicated in memory access and unification. The findings are discussed with regard to their correspondence with findings from single-word presentations and with regard to neurocognitive models of visual word recognition, semantic processing, and eye movement control during reading. PMID:27365297

Temporal variability in shell mound formation at Albatross Bay, northern Australia

PubMed Central

Petchey, Fiona; Allely, Kasey; Shiner, Justin I.; Bailey, Geoffrey

2017-01-01

We report the results of 212 radiocarbon determinations from the archaeological excavation of 70 shell mound deposits in the Wathayn region of Albatross Bay, Australia. This is an intensive study of a closely co-located group of mounds within a geographically restricted area in a wider region where many more shell mounds have been reported. Valves from the bivalve Tegillarca granosa (Linnaeus, 1758) were dated. The dates obtained are used to calculate rates of accumulation for the shell mound deposits. These demonstrate highly variable rates of accumulation both within and between mounds. We assess these results in relation to likely mechanisms of shell deposition and show that rates of deposition are affected by time-dependent processes both during the accumulation of shell deposits and during their subsequent deformation. This complicates the interpretation of the rates at which shell mound deposits appear to have accumulated. At Wathayn, there is little temporal or spatial consistency in the rates at which mounds accumulated. Comparisons between the Wathayn results and those obtained from shell deposits elsewhere, both in the wider Albatross Bay region and worldwide, suggest the need for caution when deriving behavioural inferences from shell mound deposition rates, and the need for more comprehensive sampling of individual mounds and groups of mounds. PMID:28854234

Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality

PubMed Central

Riccelli, Roberta; Toschi, Nicola; Nigro, Salvatore; Terracciano, Antonio

2017-01-01

Abstract The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project. Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal–temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal–parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders. PMID:28122961

Using monitoring data to map amphibian breeding hotspots and describe wetland vulnerability in Yellowstone and Grand Teton National Parks

USGS Publications Warehouse

Ray, Andrew M.; Legg, Kristin; Sepulveda, Adam; Hossack, Blake R.; Patla, Debra

2015-01-01

Amphibians have been selected as a “vital sign” by several National Park Service (NPS) Inventory and Monitoring (I&M) networks. An eight-year amphibian monitoring data set provided opportunities to examine spatial and temporal patterns in amphibian breeding richness and wetland desiccation across Yellowstone and Grand Teton National Parks. Amphibian breeding richness was variable across both parks and only four of 31 permanent monitoring catchments contained all four widely distributed species. Annual breeding richness was also variable through time and fluctuated by as much as 75% in some years and catchments. Wetland desiccation was also documented across the region, but alone did not explain variations in amphibian richness. High annual variability across the region emphasizes the need for multiple years of monitoring to accurately describe amphibian richness and wetland desiccation dynamics.

Biophysical Variables Retrieval Over Russian Winter Wheat Fields Using Medium Resolution

NASA Astrophysics Data System (ADS)

d'Andrimont, Raphael; Waldner, Francois; Bartalev, Sergey; Plotnikov, Dmitry; Kleschenko, Alexander; Virchenko, Oleg; de Wit, Allard; Roerink, Gerbert; Defourny, Pierre

2013-12-01

Winter wheat production in the Russian Federation represents one of the sources of uncertainty for the international commodity market. In particular, adverse weather conditions may induce winter kill resulting in large yields' losses. Improving the monitoring of winter- wheat in Russia with a focus on winter-kill damage and its impacts on yield is thus a key challenge.This paper presents the methods and the results of the biophysical variables retrieval on a daily basis as an input for crop growth modeling at parcel level over a 10-years period (2003-2012) in the Russian context. The field campaigns carried out on 2 sites in the Tula region from 2010 to 2012 shows that it is possible to characterize the spatial and temporal variability at pixel, field and regional scale using medium resolution sensors (MODIS) over Russian fields.

Exploring spatial-temporal dynamics of fire regime features in mainland Spain

NASA Astrophysics Data System (ADS)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

Local disturbance cycles and the maintenance of heterogeneity across scales in marine metapopulations.

PubMed

Gouhier, Tarik C; Guichard, Frédéric

2007-03-01

In marine systems, the occurrence and implications of disturbance-recovery cycles have been revealed at the landscape level, but only in demographically open or closed systems where landscape-level dynamics are assumed to have no feedback effect on regional dynamics. We present a mussel metapopulation model to elucidate the role of landscape-level disturbance cycles for regional response of mussel populations to onshore productivity and larval transport. Landscape dynamics are generated through spatially explicit rules, and each landscape is connected to its neighbor through unidirectional larval dispersal. The role of landscape disturbance cycles in the regional system behavior is elucidated (1) in demographically open vs. demographically coupled systems, in relation to (2) onshore reproductive output and (3) the temporal scale of landscape disturbance dynamics. By controlling for spatial structure at the landscape and metapopulation levels, we first demonstrate the interaction between landscape and oceanographic connectivity. The temporal scale of disturbance cycles, as controlled by mussel colonization rate, plays a critical role in the regional behavior of the system. Indeed, fast disturbance cycles are responsible for regional synchrony in relation to onshore reproductive output. Slow disturbance cycles, however, lead to increased robustness to changes in productivity and to demographic coupling. These testable predictions indicate that the occurrence and temporal scale of local disturbance-recovery dynamics can drive large-scale variability in demographically open systems, and the response of metapopulations to changes in nearshore productivity.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

Spatial and temporal patterns of burned area over Brazilian Cerrado from 2005 to 2015 using remote sensing data

NASA Astrophysics Data System (ADS)

Libonati, Renata; DaCamara, Carlos; Setzer, Alberto

2016-04-01

Although Cerrado is a fire-dependent biome, current agriculture practices have significantly modified the native fire regime. Moreover, over the last decades, climate conditions, such as intensive droughts, have contributed to enhance the effects of anthropogenic activities, and consequently fire, over the region. For instance, during the 2010 extreme drought there was an increase of 100% in the number of fire pixels detected by just one polar orbiting satellite (information online at http://www.cptec.inpe.br/queimadas). A better characterization of spatial and temporal fire patterns over Cerrado is therefore crucial to uncover both climate and anthropogenic influences in this ecosystem. Additionally, information about the extent, location and time of burned areas (BA) over Cerrado is especially useful to a wide range of users, from government agencies, research groups and ecologists, to fire managers and NGOs. Instruments on-board satellites are the only available operational means to collect BA data at appropriated spatial and temporal scales and in a cost-effective way. Several global BA products derived from remote sensed information have been developed over the last years using a variety of techniques based on different spatial, spectral and temporal resolutions. Although presenting similar inter-annual variability, there are marked differences among the products both in magnitude and location of the area burnt. The development of regional algorithms which take into account local characteristics such as vegetation type, soil and climate is therefore an added value to the existing information. We present a monthly BA product (AQM) for Brazil based on information from MODIS 1km. The algorithm was specifically designed for ecosystems in Brazil and the procedure represents the first initiative of an automated method for BA monitoring using remote sensing information in the country. The product relies on an algorithm that takes advantage of the ability of MIR reflectances to discriminate BA. Validation over Cerrado biome indicates that the product is in accordance with BA maps from reference data, making the product suitable for applications in fire emission studies and ecosystem management. The AQM regional database covers the 11-year period 2005-2015 over Cerrado and allows analyzing the overall temporal and spatial distribution patterns of BA for the last decade. The highest monthly mean amount is observed in September, followed by October, and March presents the lowest amount. The most severe year is 2007, followed by 2005 and 2010; 2006 and 2009 are the years with less area burned, followed by 2008. The spatial pattern of BA shows that the north region of Cerrado presents the highest frequency of occurrence. The intra and inter-annual variability of BA over Cerrado are closely related to variability of precipitation but it is worth emphasizing that, despite the major role played by climate conditions, the human factor has also a prominent role on fire dynamics in this region and cannot be disregarded.

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability.

PubMed

Ghan, Steven; Wang, Minghuai; Zhang, Shipeng; Ferrachat, Sylvaine; Gettelman, Andrew; Griesfeller, Jan; Kipling, Zak; Lohmann, Ulrike; Morrison, Hugh; Neubauer, David; Partridge, Daniel G; Stier, Philip; Takemura, Toshihiko; Wang, Hailong; Zhang, Kai

2016-05-24

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

PubMed Central

Ghan, Steven; Wang, Minghuai; Zhang, Shipeng; Ferrachat, Sylvaine; Gettelman, Andrew; Griesfeller, Jan; Kipling, Zak; Lohmann, Ulrike; Morrison, Hugh; Neubauer, David; Partridge, Daniel G.; Stier, Philip; Takemura, Toshihiko; Wang, Hailong; Zhang, Kai

2016-01-01

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing. PMID:26921324

Decadal Variability of Temperature and Salinity in the Northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Mishonov, A. V.; Seidov, D.; Reagan, J. R.; Boyer, T.; Parsons, A. R.

2017-12-01

There are only a few regions in the World Ocean where the density of observations collected over the past 60 years is sufficient for reliable data mapping with spatial resolutions finer than one-degree. The Northwest Atlantic basin is one such regions where a spatial resolution of gridded temperature and salinity fields, comparable to those generated by eddy-resolving numerical models of ocean circulation, has recently becomes available. Using the new high-resolution Northwest Atlantic Regional Climatology, built on quarter-degree and one-tenth-degree resolution fields, we analyzed decadal variability and trends of temperature and salinity over 60 years in the Northwest Atlantic, and two 30-year ocean climates of 1955-1984 and 1985-2012 to evaluate the oceanic climate shift in this region. The 30-year climate shift is demonstrated using an innovative 3-D visualization of temperature and salinity. Spatial and temporal variability of heat accumulation found in previous research of the entire North Atlantic Ocean persists in the Northwest Atlantic Ocean. Salinity changes between two 30-year climates were also computed and are discussed.

Nong Thale Pron - a key site from southern Thailand for studying monsoon variability during the past 15000 years

NASA Astrophysics Data System (ADS)

Bredberg, Camilla; Chawchai, Sakonvan; Chabangborn, Akkaneewut; Kylander, Malin; Fritz, Sherilyn; Reimer, Paula J.; Wohlfarth, Barbara

2014-05-01

Studies of marine sediments, cave speleothemes, annually laminated corals, and tree rings from Asian monsoon regions have added knowledge to our understanding of the factors that control inter-annual to millennial monsoon variability in the past and have provided important constraints for climate modeling scenarios. In contrast, the spatial and temporal pattern of sub-millennial scale monsoon variability and its impact on land cover in SE Asia are still unresolved. This shortcoming stems from the fact that temporally well-resolved paleo-environmental studies are missing from large parts of SE Asia, especially from Thailand. Given that global and regional climate models are increasingly using terrestrial paleo- data to test their performance, past changes in land cover are therefore important variables to better understand feedbacks between different Earth systems. We obtained sediments from Lake Nong Thale Pron, in southern Thailand (8º 10`N, 99 º23`E; 380 m.asl). The aim of our study is to reconstruct lake status changes and to evaluate whether the extent of these changes are linked to known shifts in monsoon intensity and variability. Preliminary results show that lake infilling started more than 15,000 years ago and that the sediments cover the last deglaciation and the Holocene. Current analyses include Itrax XRF core scanning, loss-on-ignition (LOI at 950 and 550ºC), CN elemental and isotopic composition. We expect that our results will be able to give a picture of how the lake's status has changed over time and whether the extent of these changes is linked to known shifts in monsoon intensity and variability.

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

Temporal and spatial changes in plankton respiration and biomass in the Canary Islands region: the effect of mesoscale variability

NASA Astrophysics Data System (ADS)

Arístegui, Javier; Montero, María F.

2005-02-01

The temporal and spatial variabilities in the abundance and respiratory activity of plankton communities (<200 μm) were studied during three seasonal cruises around Gran Canaria Island (Canary Islands), a region of high mesoscale variability. Marked seasonal changes in respiratory activity, plankton community structure, and the ratio of heterotrophic to autotrophic biomass can be largely explained by hydrographic changes at the mesoscale level. Wind/current shearing at the flanks of the island enhances plankton respiration, presumably as the consequence of an increase in turbulence. Counter-paired cyclonic and anticyclonic eddies generated downstream of the island act as a two-way biological pump, increasing plankton production by nutrient pumping into the euphotic zone and accelerating the transport of organic matter into the aphotic zone, respectively. Coastal upwelling waters invading the Canary region in the form of filaments can transport either water with low plankton respiration and large phytoplankton cells or water with high respiratory rates associated with small cells. Plankton respiration was closely related to the abundance of Synechococcus type cyanobacteria and heterotrophic nanoflagellates during the three periods, but was only correlated with chlorophyll during the most fertile season, suggesting that respiration was mainly linked to microbial food web processes. Size-fractionated studies showed that 51-67% of the respiratory activity was due to picoplankton cells (<2 μm). Respiration rates (average values: 113±18 to 187±87 mmol C m -2 d -1) matched primary production rates during the fertile period, but were up to one order of magnitude higher during the rest of the year. Substantial inputs of organic matter from the coastal upwelling would be necessary to balance the large annual heterotrophic deficit in the region of study.

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Baseline Brain Activity Changes in Patients With Single and Relapsing Optic Neuritis.

PubMed

Ren, Zhuoqiong; Liu, Yaou; Li, Kuncheng; Duan, Yunyun; Jing, Huang; Liang, Peipeng; Sun, Zheng; Zhang, Xiaojun; Mao, Bei

2018-01-01

Purpose : To investigate spontaneous brain activity amplitude alterations in single and relapsing optic neuritis (sON and rON, respectively) and their relationships with clinical variables. Methods : In total, 42 patients with sON, 35 patients with rON and 50 healthy volunteers were recruited. Resting-state functional Magnetic Resonance Imaging (rs-fMRI) scans were acquired for all participants and compared to investigate the changes in the amplitude of low-frequency fluctuations (ALFFs) among the three groups. The relationships between the ALFFs in regions with significant differences in the groups and clinical variables, including the logarithm of minimal angle of resolution (LogMAR), Expanded Disability Status Scale (EDSS) score and disease duration, were further explored. Results : Compared with healthy volunteers, the sON and rON patients showed significantly decreased ALFFs in several regions of the occipital and temporal lobes (i.e., inferior occipital gyrus and superior temporal gyrus; corrected p < 0.01 using AlphaSim). The sON patients showed significantly increased ALFFs in the left caudate and certain regions in the frontal lobes (i.e., medial frontal gyrus), whereas the rON patients showed increased ALFFs in the bilateral inferior temporal gyrus and left medial frontal gyrus (corrected p < 0.01 using AlphaSim). Significantly decreased ALFFs were observed in the right inferior parietal lobule (IPL), left posterior cingulate and precuneus in the rON patients compared with those in the sON patients (corrected p < 0.01 using AlphaSim). Significant correlations were observed between the disease duration and ALFF in the left middle temporal gyrus, left inferior occipital gyrus, right lingual gyrus and right IPL ( p < 0.05). Conclusion : Functional impairment and adaptation occurred in both the sON and rON patients. Impairment mainly involved the occipital cortex, and functional adaptions predominantly occurred in the frontal lobe. Functional damage was more severe in the rON patients than in the sON patients and correlated with the disease duration.

A precipitation regionalization and regime for Iran based on multivariate analysis

NASA Astrophysics Data System (ADS)

Raziei, Tayeb

2018-02-01

Monthly precipitation time series of 155 synoptic stations distributed over Iran, covering 1990-2014 time period, were used to identify areas with different precipitation time variability and regimes utilizing S-mode principal component analysis (PCA) and cluster analysis (CA) preceded by T-mode PCA, respectively. Taking into account the maximum loading values of the rotated components, the first approach revealed five sub-regions characterized by different precipitation time variability, while the second method delineated eight sub-regions featured with different precipitation regimes. The sub-regions identified by the two used methods, although partly overlapping, are different considering their areal extent and complement each other as they are useful for different purposes and applications. Northwestern Iran and the Caspian Sea area were found as the two most distinctive Iranian precipitation sub-regions considering both time variability and precipitation regime since they were well captured with relatively identical areas by the two used approaches. However, the areal extents of the other three sub-regions identified by the first approach were not coincident with the coverage of their counterpart sub-regions defined by the second approach. Results suggest that the precipitation sub-region identified by the two methods would not be necessarily the same, as the first method which accounts for the variance of the data grouped stations with similar temporal variability while the second one which considers a fixed climatology defined by the average over the period 1990-2014 clusters stations having a similar march of monthly precipitation.

Airborne black carbon concentrations over an urban region in western India-temporal variability, effects of meteorology, and source regions.

PubMed

Bapna, Mukund; Sunder Raman, Ramya; Ramachandran, S; Rajesh, T A

2013-03-01

This study characterizes over 5 years of high time resolution (5 min), airborne black carbon (BC) concentrations (July 2003 to December 2008) measured over Ahmedabad, an urban region in western India. The data were used to obtain different time averages of BC concentrations, and these averages were then used to assess the diurnal, seasonal, and annual variability of BC over the study region. Assessment of diurnal variations revealed a strong association between BC concentrations and vehicular traffic. Peaks in BC concentration were co-incident with the morning (0730 to 0830, LST) and late evening (1930 to 2030, LST) rush hour traffic. Additionally, diurnal variability in BC concentrations during major festivals (Diwali and Dushera during the months of October/November) revealed an increase in BC concentrations due to fireworks displays. Maximum half hourly BC concentrations during the festival days were as high as 79.8 μg m(-3). However, the high concentrations rapidly decayed suggesting that local meteorology during the festive season was favorable for aerosol dispersion. A multiple linear regression (MLR) model with BC as the dependent variable and meteorological parameters as independent variables was fitted. The variability in temperature, humidity, wind speed, and wind direction accounted for about 49% of the variability in measured BC concentrations. Conditional probability function (CPF) analysis was used to identify the geographical location of local source regions contributing to the effective BC measured (at 880 nm) at the receptor site. The east north-east (ENE) direction to the receptor was identified as a major source region. National highway (NH8) and two coal-fired thermal power stations (at Gandhinagar and Sabarmati) were located in the identified direction, suggesting that local traffic and power plant emissions were likely contributors to the measured BC.

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Regional flood-frequency relations for streams with many years of no flow

USGS Publications Warehouse

Hjalmarson, Hjalmar W.; Thomas, Blakemore E.; ,

1990-01-01

In the southwestern United States, flood-frequency relations for streams that drain small arid basins are difficult to estimate, largely because of the extreme temporal and spatial variability of floods and the many years of no flow. A method is proposed that is based on the station-year method. The new method produces regional flood-frequency relations using all available annual peak-discharge data. The prediction errors for the relations are directly assessed using randomly selected subsamples of the annual peak discharges.

The fuelbed: a key element of the Fuel Characteristic Classification System.

Treesearch

Cynthia L. Riccardi; Roger D. Ottmar; David V. Sandberg; Anne Andreu; Ella Elman; Karen Kopper; Jennifer Long

2007-01-01

Wildland fuelbed characteristics are temporally and spatially complex and can vary widely across regions. To capture this variability, we designed the Fuel Characteristic Classification System (FCCS), a national system to create fuelbeds and classify those fuelbeds for their capacity to support fire and consume fuels. This paper describes the structure of the fuelbeds...

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

Spatial and temporal characteristics of droughts in Luanhe River basin, China

NASA Astrophysics Data System (ADS)

Wang, Yixuan; Zhang, Ting; Chen, Xu; Li, Jianzhu; Feng, Ping

2018-02-01

The spatial and temporal characteristics of drought are investigated for Luanhe River basin, using monthly precipitation data from 26 stations covering the common period of 1958-2011. The spatial pattern of drought was assessed by applying principal component analysis (PCA) to the Standardized Precipitation Index (SPI) computed on 3- and 12-month time scales. In addition, annual SPI and seasonal SPIs (including spring SPI, summer SPI, autumn SPI, and winter SPI) were also defined and considered in this study to characterize seasonal and annual drought conditions, respectively. For all seven SPI cases, three distinctive sub-regions with different temporal evolutions of droughts are well identified, respectively, representing the southeast, middle, and northwest of the Luanhe River basin. The Mann-Kendall (MK) trend test with a trend-free pre-whitening (TFPW) procedure and Sen's method were used to determine the temporal trends in the annual and seasonal SPI time series. The continuous wavelet transform (CWT) was employed for further detecting the periodical features of drought condition in each sub-region. Results of MK and Sen's tests show a general tendency of intensification in summer drought over the entire basin, while a significant mitigating trend in spring drought. On the whole, an aggravating trend of inter-annual drought is discovered across the basin. Based on the CWT, the drought variability in the basin is generally dominated by 16- to 64-month cycles, and the 2- to 6-year cycles appear to be obvious when concerned with annual and seasonal droughts. Furthermore, a cross wavelet analysis was performed to examine the possible links between the drought conditions and large-scale climate patterns. The teleconnections of ENSO, NAO, PDO, and AMO show significant influences on the regional droughts principally concentrated in the 16- to 64-month period, maybe responsible for the physical causes of the cyclical behavior of drought occurrences. PDO and AMO also highlight a noteworthy correlation with drought variability on a decadal scale (around 128-month period). The findings of this study will provide valuable references for regional drought mitigation and water resource management.

Spatial synchrony of malaria outbreaks in a highland region of Ethiopia.

PubMed

Wimberly, Michael C; Midekisa, Alemayehu; Semuniguse, Paulos; Teka, Hiwot; Henebry, Geoffrey M; Chuang, Ting-Wu; Senay, Gabriel B

2012-10-01

To understand the drivers and consequences of malaria in epidemic-prone regions, it is important to know whether epidemics emerge independently in different areas as a consequence of local contingencies, or whether they are synchronised across larger regions as a result of climatic fluctuations and other broad-scale drivers. To address this question, we collected historical malaria surveillance data for the Amhara region of Ethiopia and analysed them to assess the consistency of various indicators of malaria risk and determine the dominant spatial and temporal patterns of malaria within the region. We collected data from a total of 49 districts from 1999-2010. Data availability was better for more recent years and more data were available for clinically diagnosed outpatient malaria cases than confirmed malaria cases. Temporal patterns of outpatient malaria case counts were correlated with the proportion of outpatients diagnosed with malaria and confirmed malaria case counts. The proportion of outpatients diagnosed with malaria was spatially clustered, and these cluster locations were generally consistent from year to year. Outpatient malaria cases exhibited spatial synchrony at distances up to 300 km, supporting the hypothesis that regional climatic variability is an important driver of epidemics. Our results suggest that decomposing malaria risk into separate spatial and temporal components may be an effective strategy for modelling and forecasting malaria risk across large areas. They also emphasise both the value and limitations of working with historical surveillance datasets and highlight the importance of enhancing existing surveillance efforts. © 2012 Blackwell Publishing Ltd.

Spatial and temporal variability of fluoride concentrations in groundwater resources of Larestan and Gerash regions in Iran from 2003 to 2010.

PubMed

Amini, Hassan; Haghighat, Gholam Ali; Yunesian, Masud; Nabizadeh, Ramin; Mahvi, Amir Hossein; Dehghani, Mohammad Hadi; Davani, Rahim; Aminian, Abd-Rasool; Shamsipour, Mansour; Hassanzadeh, Naser; Faramarzi, Hossein; Mesdaghinia, Alireza

2016-02-01

There is discrepancy about intervals of fluoride monitoring in groundwater resources by Iranian authorities. Spatial and temporal variability of fluoride in groundwater resources of Larestan and Gerash regions in Iran were analyzed from 2003 to 2010 using a geospatial information system and the Mann-Kendall trend test. The mean concentrations of fluoride for the 8-year period in the eight cities and 31 villages were 1.6 and 2.0 mg/l, respectively; the maximum values were 2.4 and 3.8 mg/l, respectively. Spatial, temporal, and spatiotemporal variability of fluoride in overall groundwater resources were relatively constant over the years. However, results of the Mann-Kendall trend test revealed a monotonic trend in the time series of one city and 11 villages for the 8-year period. Specifically, one city and three villages showed positive significant Kendall's Tau values, suggesting an upward trend in fluoride concentrations over the 8-year period. In contrast, seven villages displayed negative significant Kendall's Tau values, arguing for a downward trend in fluoride concentrations over the years. From 2003 to 2010, approximately 52 % of the Larestan and Gerash areas have had fluoride concentrations above the maximum permissible Iranian drinking water standard fluoride level (1.4 mg/l), and about 116,000 people were exposed to such excess amounts. Therefore, our study supports for a close monitoring of fluoride concentrations from health authorities in monthly intervals, especially in villages and cities that showed positive trend in fluoride concentrations. Moreover, we recommend simultaneous implementation of cost-effective protective measures or interventions until a standard fluoride level is achieved.

Investigating the neural bases for intra-subject cognitive efficiency changes using functional magnetic resonance imaging

PubMed Central

Rao, Neena K.; Motes, Michael A.; Rypma, Bart

2014-01-01

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals. PMID:25374527

Investigating the neural bases for intra-subject cognitive efficiency changes using functional magnetic resonance imaging.

PubMed

Rao, Neena K; Motes, Michael A; Rypma, Bart

2014-01-01

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Regionalization of monthly rainfall erosivity patternsin Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June-September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000-2013)

NASA Astrophysics Data System (ADS)

Alexander, P. M.; Tedesco, M.; Fettweis, X.; van de Wal, R. S. W.; Smeets, C. J. P. P.; van den Broeke, M. R.

2014-12-01

Accurate measurements and simulations of Greenland Ice Sheet (GrIS) surface albedo are essential, given the role of surface albedo in modulating the amount of absorbed solar radiation and meltwater production. In this study, we assess the spatio-temporal variability of GrIS albedo during June, July, and August (JJA) for the period 2000-2013. We use two remote sensing products derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as outputs from the Modèle Atmosphérique Régionale (MAR) regional climate model (RCM) and data from in situ automatic weather stations. Our results point to an overall consistency in spatio-temporal variability between remote sensing and RCM albedo, but reveal a difference in mean albedo of up to ~0.08 between the two remote sensing products north of 70° N. At low elevations, albedo values simulated by the RCM are positively biased with respect to remote sensing products by up to ~0.1 and exhibit low variability compared with observations. We infer that these differences are the result of a positive bias in simulated bare ice albedo. MODIS albedo, RCM outputs, and in situ observations consistently indicate a decrease in albedo of -0.03 to -0.06 per decade over the period 2003-2013 for the GrIS ablation area. Nevertheless, satellite products show a decline in JJA albedo of -0.03 to -0.04 per decade for regions within the accumulation area that is not confirmed by either the model or in situ observations. These findings appear to contradict a previous study that found an agreement between in situ and MODIS trends for individual months. The results indicate a need for further evaluation of high elevation albedo trends, a reconciliation of MODIS mean albedo at high latitudes, and the importance of accurately simulating bare ice albedo in RCMs.

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.

Rightward dominance in temporal high-frequency electrical asymmetry corresponds to higher resting heart rate and lower baroreflex sensitivity in a heterogeneous population.

PubMed

Tegeler, Charles H; Shaltout, Hossam A; Tegeler, Catherine L; Gerdes, Lee; Lee, Sung W

2015-06-01

Explore potential use of a temporal lobe electrical asymmetry score to discriminate between sympathetic and parasympathetic tendencies in autonomic cardiovascular regulation. 131 individuals (82 women, mean age 43.1, range 13-83) with diverse clinical conditions completed inventories for depressive (CES-D or BDI-II) and insomnia-related (ISI) symptomatology, and underwent five-minute recordings of heart rate and blood pressure, allowing calculation of heart rate variability and baroreflex sensitivity (BRS), followed by one-minute, two-channel, eyes-closed scalp recordings of brain electrical activity. A temporal lobe high-frequency (23-36 Hz) electrical asymmetry score was calculated for each subject by subtracting the average amplitude in the left temporal region from amplitude in the right temporal region, and dividing by the lesser of the two. Depressive and insomnia-related symptomatology exceeding clinical threshold levels were reported by 48% and 50% of subjects, respectively. Using a cutoff value of 5% or greater to define temporal high-frequency asymmetry, subjects with leftward compared to rightward asymmetry were more likely to report use of a sedative-hypnotic medication (42% vs. 22%, P = 0.02). Among subjects with asymmetry of 5% or greater to 30% or greater, those with rightward compared to leftward temporal high-frequency asymmetry had higher resting heart rate (≥5% asymmetry, 72.3 vs. 63.8, P = 0.004; ≥10%, 71.5 vs. 63.0, P = 0.01; ≥20%, 72.2 vs. 64.2, P = 0.05; ≥30%, 71.4 vs. 64.6, P = 0.05). Subjects with larger degrees of rightward compared to leftward temporal high-frequency asymmetry had lower baroreflex sensitivity (≥40% asymmetry, 10.6 vs. 16.4, P = 0.03; ≥50% asymmetry, 10.4 vs. 16.7, P = 0.05). In a heterogeneous population, individuals with rightward compared to leftward temporal high-frequency electrical asymmetry had higher resting heart rate and lower BRS. Two-channel recording of brain electrical activity from bilateral temporal regions appears to hold promise for further investigation as a means to assess cortical activity associated with autonomic cardiovascular regulation.

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

Millennial-scale variability in the local radiocarbon reservoir age of the Florida Keys reef tract during the Holocene

NASA Astrophysics Data System (ADS)

Ashe, E.; Toth, L. T.; Cheng, H.; Edwards, R. L.; Richey, J. N.

2016-12-01

The oceanic passage between the Florida Keys and Cuba, known as the Straits of Florida, provides a critical connection between the tropics and northern Atlantic. Changes in the character of water masses transported through this region may ultimately have important impacts on high-latitude climate variability. Although recent studies have documented significant changes in the density of regional surface waters over millennial timescales, little is known about the contribution of local- to regional-scale changes in circulation to surface-water variability. Local variability in the radiocarbon age, ΔR, of surface waters can be used to trace changes in local water-column mixing and/or changes in regional source water over a variety of spatial and temporal scales. We reconstructed "snapshots" of ΔR variability across the Florida Keys reef tract during the last 10,000 years by dating 68 unaltered corals collected from Holocene reef cores with both U-series and radiocarbon techniques. We combined the snapshots of ΔR into a semi-empirical model to develop a robust statistical reconstruction of millennial-scale variability in ΔR on the Florida Keys reef tract. Our model demonstrates that ΔR varied significantly during the Holocene, with relatively high values during the early Holocene and around 3000 years BP and relatively low values around 7000 years BP and at present. We compare the trends in ΔR to existing paleoceanographic reconstructions to evaluate the relative contribution of local upwelling versus changes in source water to the region as a whole in driving local radiocarbon variability, and discuss the importance of these results to our understanding of regional-scale oceanographic and climatic variability during the Holocene. We also discuss the implications of our results for radiocarbon dating of marine samples from south Florida and present a model of ΔR versus 14C age that can be used to improve the accuracy of radiocarbon calibrations from this region.

Uncertainty evaluation of a regional real-time system for rain-induced landslides

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

2015-04-01

A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

Determining hydroclimatic extreme events over the south-central Andes

NASA Astrophysics Data System (ADS)

RamezaniZiarani, Maryam; Bookhagen, Bodo; Schmidt, Torsten; Wickert, Jens; de la Torre, Alejandro; Volkholz, Jan

2017-04-01

The south-central Andes in NW Argentina are characterized by a strong rainfall asymmetry. In the east-west direction exists one of the steepest rainfall gradients on Earth, resulting from the large topographic differences in this region. In addition, in the north-south direction the rainfall intensity varies as the climatic regime shifts from the tropical central Andes to the subtropical south-central Andes. In this study, we investigate hydroclimatic extreme events over the south-central Andes using ERA-Interim reanalysis data of the ECMWF (European Centre for Medium-Range Weather Forecasts), the high resolution regional climate model (COSMO-CLM) data and TRMM (Tropical Rainfall Measuring Mission) data. We divide the area in three different study regions based on elevation: The high-elevation Altiplano-Puna plateau, an intermediate area characterized by intramontane basins, and the foreland area. We analyze the correlations between climatic variables, such as specific humidity, zonal wind component, meridional wind component and extreme rainfall events in all three domains. The results show that there is a high positive temporal correlation between extreme rainfall events (90th and 99th percentile rainfall) and extreme specific humidity events (90th and 99th percentile specific humidity). In addition, the temporal variations analysis represents a trend of increasing specific humidity with time during time period (1994-2013) over the Altiplano-Puna plateau which is in agreement with rainfall trend. Regarding zonal winds, our results indicate that 99th percentile rainfall events over the Altiplano-Puna plateau coincide temporally with strong easterly winds from intermountain and foreland regions in the east. In addition, the results regarding the meridional wind component represent strong northerly winds in the foreland region coincide temporally with 99th percentile rainfall over the Altiplano-Puna plateau.

Lightning Forcing in Global Fire Models: The Importance of Temporal Resolution

NASA Astrophysics Data System (ADS)

Felsberg, A.; Kloster, S.; Wilkenskjeld, S.; Krause, A.; Lasslop, G.

2018-01-01

In global fire models, lightning is typically prescribed from observational data with monthly mean temporal resolution while meteorological forcings, such as precipitation or temperature, are prescribed in a daily resolution. In this study, we investigate the importance of the temporal resolution of the lightning forcing for the simulation of burned area by varying from daily to monthly and annual mean forcing. For this, we utilize the vegetation fire model JSBACH-SPITFIRE to simulate burned area, forced with meteorological and lightning data derived from the general circulation model ECHAM6. On a global scale, differences in burned area caused by lightning forcing applied in coarser temporal resolution stay below 0.55% compared to the use of daily mean forcing. Regionally, however, differences reach up to 100%, depending on the region and season. Monthly averaged lightning forcing as well as the monthly lightning climatology cause differences through an interaction between lightning ignitions and fire prone weather conditions, accounted for by the fire danger index. This interaction leads to decreased burned area in the boreal zone and increased burned area in the Tropics and Subtropics under the coarser temporal resolution. The exclusion of interannual variability, when forced with the lightning climatology, has only a minor impact on the simulated burned area. Annually averaged lightning forcing causes differences as a direct result of the eliminated seasonal characteristics of lightning. Burned area is decreased in summer and increased in winter where fuel is available. Regions with little seasonality, such as the Tropics and Subtropics, experience an increase in burned area.

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites

PubMed Central

Karl, Jason W.

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral ‘fingerprint’ of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches. PMID:28414731

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.

PubMed

Maynard, Jonathan J; Karl, Jason W

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral 'fingerprint' of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches.

Temporal and spatial variation in pharmaceutical concentrations in an urban river system.

PubMed

Burns, Emily E; Carter, Laura J; Kolpin, Dana W; Thomas-Oates, Jane; Boxall, Alistair B A

2018-06-15

Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse. Copyright © 2018 Elsevier Ltd. All rights reserved.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

PubMed

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-06-14

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably.

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

NASA Astrophysics Data System (ADS)

Blauw, Anouk N.; Benincà, Elisa; Laane, Remi W. P. M.; Greenwood, Naomi; Huisman, Jef

2018-02-01

Phytoplankton concentrations display strong temporal variability at different time scales. Recent advances in automated moorings enable detailed investigation of this variability. In this study, we analyzed phytoplankton fluctuations at four automated mooring stations in the North Sea, which measured phytoplankton abundance (chlorophyll) and several environmental variables at a temporal resolution of 12-30 min for two to nine years. The stations differed in tidal range, water depth and freshwater influence. This allowed comparison of the predictability and environmental drivers of phytoplankton variability across different time scales and geographical regions. We analyzed the time series using wavelet analysis, cross correlations and generalized additive models to quantify the response of chlorophyll fluorescence to various environmental variables (tidal and meteorological variables, salinity, suspended particulate matter, nitrate and sea surface temperature). Hour-to-hour and day-to-day fluctuations in chlorophyll fluorescence were substantial, and mainly driven by sinking and vertical mixing of phytoplankton cells, horizontal transport of different water masses, and non-photochemical quenching of the fluorescence signal. At the macro-tidal stations, these short-term phytoplankton fluctuations were strongly driven by the tides. Along the Dutch coast, variation in salinity associated with the freshwater influence of the river Rhine played an important role, while in the central North Sea variation in weather conditions was a major determinant of phytoplankton variability. At time scales of weeks to months, solar irradiance, nutrient conditions and thermal stratification were the dominant drivers of changes in chlorophyll concentrations. These results show that the dominant drivers of phytoplankton fluctuations differ across marine environments and time scales. Moreover, our findings show that phytoplankton variability on hourly to daily time scales should not be dismissed as environmental noise, but is related to vertical and horizontal particle transport driven by winds and tides. Quantification of these transport processes contributes to an improved predictability of marine phytoplankton concentrations.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

PubMed Central

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-01-01

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably. PMID:27314369

Time-series Oxygen-18 Precipitation Isoscapes for Canada and the Northern United States

NASA Astrophysics Data System (ADS)

Delavau, Carly J.; Chun, Kwok P.; Stadnyk, Tricia A.; Birks, S. Jean; Welker, Jeffrey M.

2014-05-01

The present and past hydrological cycle from the watershed to regional scale can be greatly enhanced using water isotopes (δ18O and δ2H), displayed today as isoscapes. The development of water isoscapes has both hydrological and ecological applications, such as ground water recharge and food web ecology, and can provide critical information when observations are not available due to spatial and temporal gaps in sampling and data networks. This study focuses on the creation of δ18O precipitation (δ18Oppt) isoscapes at a monthly temporal frequency across Canada and the northern United States (US) utilizing CNIP (Canadian Network for Isotopes in Precipitation) and USNIP (United States Network for Isotopes in Precipitation) measurements. Multiple linear stepwise regressions of CNIP and USNIP observations alongside NARR (North American Regional Reanalysis) climatological variables, teleconnection indices, and geographic indicators are utilized to create empirical models that predict the δ18O of monthly precipitation across Canada and the northern US. Pooling information from nearby locations within a region can be useful due to the similarity of processes and mechanisms controlling the variability of δ18O. We expect similarity in the controls on isotopic composition to strengthen the correlation between δ18Oppt and predictor variables, resulting in model simulation improvements. For this reason, three different regionalization approaches are used to separate the study domain into 'isotope zones' to explore the effect of regionalization on model performance. This methodology results in 15 empirical models, five within each regionalization. A split sample calibration and validation approach is employed for model development, and parameter selection is based on demonstrated improvement of the Akaike Information Criteria (AIC). Simulation results indicate the empirical models are generally able to capture the overall monthly variability in δ18Oppt. For the three regionalizations, average adjusted-R2 and RMSE (weighted to number of observations within each isotope zone) range from 0.70 - 0.72 and 2.76 - 2.91, respectively, indicating that on average the different spatial groupings perform comparably. Validation weighted R2and RMSE show a larger spread between models and poorer performance, ranging from 0.45 - 0.59 and 3.28 - 3.39, respectively. Additional evaluation of simulated δ18Oppt at each station and inter/intra-annually is conducted to evaluate model performance over various space and time scales. Stepwise regression derived parameterizations indicate the significance of precipitable water content and latitude as predictor variables for all regionalizations. Long-term (1981-2010) annual average δ18Oppt isoscapes are produced for Canada and the northern US, highlighting the differences between regionalization approaches. 95% confidence interval maps are generated to provide an estimate of the uncertainty associated with long-term δ18Oppt simulations. This is the first ever time-series empirical modelling of δ18Oppt for Canada utilizing CNIP data, as well as the first modelling collaboration between the CNIP and USNIP networks. This study is the initial step towards empirically derived time-series δ18Oppt for use in iso-hydrological modelling studies. Methods and results from this research are equally applicable to ecology and forensics as the simulated δ18Oppt isoscapes provide the primary oxygen source for many plants and foodwebs at refined temporal and spatial scales across Canada and the northern US.

Environmental, biological and anthropogenic effects on grizzly bear body size: temporal and spatial considerations.

PubMed

Nielsen, Scott E; Cattet, Marc R L; Boulanger, John; Cranston, Jerome; McDermid, Greg J; Shafer, Aaron B A; Stenhouse, Gordon B

2013-09-08

Individual body growth is controlled in large part by the spatial and temporal heterogeneity of, and competition for, resources. Grizzly bears (Ursus arctos L.) are an excellent species for studying the effects of resource heterogeneity and maternal effects (i.e. silver spoon) on life history traits such as body size because their habitats are highly variable in space and time. Here, we evaluated influences on body size of grizzly bears in Alberta, Canada by testing six factors that accounted for spatial and temporal heterogeneity in environments during maternal, natal and 'capture' (recent) environments. After accounting for intrinsic biological factors (age, sex), we examined how body size, measured in mass, length and body condition, was influenced by: (a) population density; (b) regional habitat productivity; (c) inter-annual variability in productivity (including silver spoon effects); (d) local habitat quality; (e) human footprint (disturbances); and (f) landscape change. We found sex and age explained the most variance in body mass, condition and length (R(2) from 0.48-0.64). Inter-annual variability in climate the year before and of birth (silver spoon effects) had detectable effects on the three-body size metrics (R(2) from 0.04-0.07); both maternal (year before birth) and natal (year of birth) effects of precipitation and temperature were related with body size. Local heterogeneity in habitat quality also explained variance in body mass and condition (R(2) from 0.01-0.08), while annual rate of landscape change explained additional variance in body length (R(2) of 0.03). Human footprint and population density had no observed effect on body size. These results illustrated that body size patterns of grizzly bears, while largely affected by basic biological characteristics (age and sex), were also influenced by regional environmental gradients the year before, and of, the individual's birth thus illustrating silver spoon effects. The magnitude of the silver spoon effects was on par with the influence of contemporary regional habitat productivity, which showed that both temporal and spatial influences explain in part body size patterns in grizzly bears. Because smaller bears were found in colder and less-productive environments, we hypothesize that warming global temperatures may positively affect body mass of interior bears.

Effects of land use pattern on soil water in revegetation watersheds in semi-arid Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Lei; Chen, Liding; Wei, Wei

2017-04-01

Soil water stored below rainfall infiltration depth is a reliable water resource for plant growth in arid and semi-arid regions. For decreasing serious soil erosion, large-scale human-introduced vegetation restoration was initiated in Chinese Loess Plateau in late 1990s. However, these activities may result in excessive water consumption and soil water deficit if no appropriate scientific guidance were offered. This in turn impacts the regional ecological restoration and sustainable management of water resources. In this study, soil water content data in depth of 0-5 m was obtained by long-term field observation and geostatistical method in 6 small watersheds covered with different land use pattern. Profile characteristics and spatial-temporal patterns of soil water were compared between different land use types, hillslopes, and watersheds. The results showed that: (1) Introduced vegetation consumed excessive amount of water when compared with native grassland and farmland, and induced temporally stable soil desiccation in depth of 0-5 m. The introduced vegetation decreased soil water content to levels lower than the reference value representing no human impact in all soil layers. (2) The analysis of differences in soil water at hillslope and watershed scales indicated that land use determined the spatial and temporal variability of soil water. Soil water at watershed scale increased with the increasing area of farmland, and decreased with increasing percentage of introduced vegetation. Land use structure determined the soil water condition and land use pattern determined the spatial-temporal variability of soil water at watershed scale. (3) Large-scale revegetation with introduced vegetation diminished the spatial heterogeneity of soil water at different scales. Land use pattern adjustment could be used to improve the water resources management and maintain the sustainability of vegetation restoration.

Weather analysis and interpretation procedures developed for the US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Trenchard, M. H. (Principal Investigator)

1980-01-01

Procedures and techniques for providing analyses of meteorological conditions at segments during the growing season were developed for the U.S./Canada Wheat and Barley Exploratory Experiment. The main product and analysis tool is the segment-level climagraph which depicts temporally meteorological variables for the current year compared with climatological normals. The variable values for the segment are estimates derived through objective analysis of values obtained at first-order station in the region. The procedures and products documented represent a baseline for future Foreign Commodity Production Forecasting experiments.

Spatial and temporal ecological variability in the northern Gulf of Alaska: What have we learned since the Exxon Valdez oil spill?

NASA Astrophysics Data System (ADS)

Aderhold, Donna G. R.; Lindeberg, Mandy R.; Holderied, Kris; Pegau, W. Scott

2018-01-01

This special issue examines oceanographic and biological variability in the northern Gulf of Alaska region with an emphasis on recent monitoring efforts of the Gulf Watch Alaska (GWA) and Herring Research and Monitoring (HRM) programs funded by the Exxon Valdez Oil Spill Trustee Council (EVOSTC). These programs are designed to improve our understanding of how changing environmental conditions affect Gulf of Alaska ecosystems and the long-term status of resources injured by the Exxon Valdez oil spill.

ENSO controls interannual fire activity in southeast Australia

NASA Astrophysics Data System (ADS)

Mariani, M.; Fletcher, M.-S.; Holz, A.; Nyman, P.

2016-10-01

El Niño-Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management.

Land change variability and human-environment dynamics in the United States Great Plains

USGS Publications Warehouse

Drummond, M.A.; Auch, Roger F.; Karstensen, K.A.; Sayler, K. L.; Taylor, Janis L.; Loveland, Thomas R.

2012-01-01

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.

2015-01-01

Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.

Cholera and shigellosis in Bangladesh: similarities and differences in population dynamics under climate forcing

NASA Astrophysics Data System (ADS)

Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.

2012-12-01

The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.

Intra-seasonal rainfall variability during the maize growing season in the northern lowlands of Lesotho

NASA Astrophysics Data System (ADS)

Tongwane, Mphethe Isaac; Moeletsi, Mokhele Edmond

2015-05-01

Intra-seasonal rainfall distribution was identified as a priority gap that needs to be addressed for southern Africa to cope with agro-meteorological risks. The region in the northwest of Lesotho is appropriate for crop cultivation due to its relatively favourable climatic conditions and soils. High rainfall variability is often blamed for poor agricultural production in this region. This study aims to determine the onset of rains, cessation of rains and rainy season duration using historical climate data. Temporal variability of these rainy season characteristics was also investigated. The earliest and latest onset dates of the rainy season are during the last week of October at Butha-Buthe and the third week of November at Mapoteng, respectively. Cessation of the season is predominantly in the first week of April making the season approximately 137-163 days long depending on the location. Average seasonal rainfall ranged from 474 mm at Mapoteng to 668 mm at Butha-Buthe. Onset and cessation of the rainfall season vary by 4-7 weeks and 1 week, respectively. Mean coefficient of variation of seasonal rainfall is 39 %, but monthly variations are higher. These variations make annual crop management and planning difficult each year. Trends show a decrease in the rainfall amounts but improvements in both the temporal distribution of annual rainfall, onset and cessation dates.

Biodiversity of suprabenthic peracarid assemblages from the Blanes Canyon region (NW Mediterranean Sea) in relation to natural disturbance and trawling pressure

NASA Astrophysics Data System (ADS)

Almeida, Mariana; Frutos, Inmaculada; Company, Joan B.; Martin, Daniel; Romano, Chiara; Cunha, Marina R.

2017-03-01

Blanes Canyon and its adjacent margin are important fishery areas (mainly by bottom trawling) located in a highly energetic oceanographic setting in the NW Mediterranean Sea. Here we assess the spatial and temporal variability in abundance, diversity and community structure of the suprabenthic peracarid assemblages in this region and examine this variability in relation to the natural and anthropogenic (trawling fisheries) disturbance regimes. The sampling was conducted between March 2003 and May 2004 in three main fishing grounds, the canyon head (average depth: 490 m), the canyon wall (average depth: 550 m) and the eastern adjacent slope (average depth: 820 m), as well as in two non-exploited areas in the western (at 900 m depth) and eastern (at 1500 m depth) slope near the canyon mouth. A total of 138 species were identified, with amphipods being the most speciose and abundant group, followed by mysids in terms of abundance. Our results show high spatial and temporal variability in suprabenthic assemblages. Densities were higher in the canyon head and western slope, which appear to be the preferential routes for water masses and particle fluxes in months of flood events, and other energetic processes. In the canyon head, where periodic erosion processes are more active, low diversity, high dominance and higher turnover (β-diversity) were observed, apparently coupled with significant temporal fluctuations in the densities of the highly motile component of suprabenthos (mysids, predatory and scavenging amphipods). In the sedimentary more stable eastern slope, high diversity values were observed, accompanied by a higher relative contribution of the less motile groups (i.e. amphipods, most isopods, cumaceans). These groups have a closer interaction with the sediment where they exploit different food sources and are more susceptible to physical disturbance. Temporal variability in their diversity may be related to changes in food quality rather than quantity. In the canyon wall, temporal fluctuations in diversity indices were only revealed in relation to the overall higher and more continued fishing pressure observed in the canyon wall fishing ground (Cara Norte/Sot site). Here, species richness and abundance declined with increasing fishing pressure but the lowest trophic and taxonomic diversities were observed under intermediate levels of disturbance. These findings underline (i) the differences between relatively low and highly motile taxa in terms of response to disturbance events; (ii) the differences between assemblages subjected to different levels of natural disturbance and trawling pressure, which modify the common bathymetric patterns of abundance and diversity often described from continental margins.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

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

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

Time dependent wind fields

NASA Technical Reports Server (NTRS)

Chelton, D. B.

1986-01-01

Two tasks were performed: (1) determination of the accuracy of Seasat scatterometer, altimeter, and scanning multichannel microwave radiometer measurements of wind speed; and (2) application of Seasat altimeter measurements of sea level to study the spatial and temporal variability of geostrophic flow in the Antarctic Circumpolar Current. The results of the first task have identified systematic errors in wind speeds estimated by all three satellite sensors. However, in all cases the errors are correctable and corrected wind speeds agree between the three sensors to better than 1 ms sup -1 in 96-day 2 deg. latitude by 6 deg. longitude averages. The second task has resulted in development of a new technique for using altimeter sea level measurements to study the temporal variability of large scale sea level variations. Application of the technique to the Antarctic Circumpolar Current yielded new information about the ocean circulation in this region of the ocean that is poorly sampled by conventional ship-based measurements.

Climate-related relative sea-level changes from Chesapeake Bay, U.S. Atlantic coast

NASA Astrophysics Data System (ADS)

Shaw, Timothy; Horton, Benjamin; Kemp, Andrew; Cahill, Niamh; Mann, Michael; Engelhart, Simon; Kopp, Robert; Brain, Matthew; Clear, Jennifer; Corbett, Reide; Nikitina, Daria; Garcia-Artola, Ane; Walker, Jennifer

2017-04-01

Proxy-based reconstructions of relative sea level (RSL) from the coastlines of the North Atlantic have revealed spatial and temporal variability in the rates of RSL rise during periods of known Late-Holocene climatic variability. Regional driving mechanisms for such variability include glacial isostatic adjustment, static-equilibrium of land-ice changes and/or ocean dynamic effects as well as more localized factors (e.g. sediment compaction and tidal range change). We present a 4000-year RSL reconstruction from salt-marsh sediments of the Chesapeake Bay using a foraminiferal-based transfer function and a composite chronology. A local contemporary training set of foraminifera was developed to calibrate fossil counterparts and provide estimates of paleo marsh elevation with vertical uncertainties of ±0.06m. A composite chronology combining 30 radiocarbon dates, pollen chronohorizons, regional pollution histories, and short-lived radionuclides was placed into a Bayesian age-depth framework yielding low temporal uncertainties averaging 40 years. A compression-only geotechnical model was applied to decompact the RSL record. We coupled the proxy reconstruction with direct observations from nearby tide gauge records before rates of RSL rise were quantified through application of an Errors-In-Variables Integrated Gaussian Process model. The RSL history for Chesapeake Bay shows 6 m of rise since 2000 BCE. Between 2000 BCE and 1300 BCE, rates of RSL increasing to 1.4 mm/yr precede a significant decrease to 0.8 mm/yr at 700 BCE. This minimum coincides with widespread climate cooling identified in multiple paleoclimate archives of the North Atlantic. An increase in the rate of RSL rise to 2.1 mm/yr at 200 CE similarly precedes a decrease in the rate of RSL rise at 1450 CE (1.3 mm/yr) that coincides with the Little Ice Age. Modern rates of RSL rise (3.6 mm/yr) are the fastest observed in the past 4000 years. The temporal length and decadal resolution of the RSL reconstruction further reconciles the response of sea levels to late Holocene climate variability.

Historical Arctic Logbooks Provide Insights into Past Diets and Climatic Responses of Cod

PubMed Central

Townhill, Bryony L.; Maxwell, David; Engelhard, Georg H.; Simpson, Stephen D.; Pinnegar, John K.

2015-01-01

Gadus morhua (Atlantic cod) stocks in the Barents Sea are currently at levels not seen since the 1950s. Causes for the population increase last century, and understanding of whether such large numbers will be maintained in the future, are unclear. To explore this, we digitised and interrogated historical cod catch and diet datasets from the Barents Sea. Seventeen years of catch data and 12 years of prey data spanning 1930–1959 cover unexplored spatial and temporal ranges, and importantly capture the end of a previous warm period, when temperatures were similar to those currently being experienced. This study aimed to evaluate cod catch per unit effort and prey frequency in relation to spatial, temporal and environmental variables. There was substantial spatio-temporal heterogeneity in catches through the time series. The highest catches were generally in the 1930s and 1940s, although at some localities more cod were recorded late in the 1950s. Generalized Additive Models showed that environmental, spatial and temporal variables are all valuable descriptors of cod catches, with the highest occurring from 15–45°E longitude and 73–77°N latitude, at bottom temperatures between 2 and 4°C and at depths between 150 and 250 m. Cod diets were highly variable during the study period, with frequent changes in the relative frequencies of different prey species, particularly Mallotus villosus (capelin). Environmental variables were particularly good at describing the importance of capelin and Clupea harengus (herring) in the diet. These new analyses support existing knowledge about how the ecology of the region is controlled by climatic variability. When viewed in combination with more recent data, these historical relationships will be valuable in forecasting the future of Barents Sea fisheries, and in understanding how environments and ecosystems may respond. PMID:26331271

Application of GRACE for Monitoring Groundwater in Data Scarce Regions

NASA Technical Reports Server (NTRS)

Rodell, Matt; Li, Bailing; Famiglietti, Jay; Zaitchik, Ben

2012-01-01

In the United States, groundwater storage is somewhat well monitored (spatial and temporal data gaps notwithstanding) and abundant data are freely and easily accessible. Outside of the U.S., groundwater often is not monitored systematically and where it is the data are rarely centralized and made available. Since 2002 the Gravity Recovery and Climate Experiment (GRACE) satellite mission has delivered gravity field observations which have been used to infer variations in total terrestrial water storage, including groundwater, at regional to continental scales. Challenges to using GRACE for groundwater monitoring include its relatively coarse spatial and temporal resolutions, its inability to differentiate groundwater from other types of water on and under the land surface, and typical 2-3 month data latency. Data assimilation can be used to overcome these challenges, but uncertainty in the results remains and is difficult to quantify without independent observations. Nevertheless, the results are preferable to the alternative - no data at all- and GRACE has already revealed groundwater variability and trends in regions where only anecdotal evidence existed previously.

Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Chen, Pin-An; Liu, Chen-Wuing; Liao, Vivian Hsiu-Chuan; Liao, Chung-Min

2013-08-01

Arsenic (As) is an odorless semi-metal that occurs naturally in rock and soil, and As contamination in groundwater resources has become a serious threat to human health. Thus, assessing the spatial and temporal variability of As concentration is highly desirable, particularly in heavily As-contaminated areas. However, various difficulties may be encountered in the regional estimation of As concentration such as cost-intensive field monitoring, scarcity of field data, identification of important factors affecting As, over-fitting or poor estimation accuracy. This study develops a novel systematical dynamic-neural modeling (SDM) for effectively estimating regional As-contaminated water quality by using easily-measured water quality variables. To tackle the difficulties commonly encountered in regional estimation, the SDM comprises of a neural network and four statistical techniques: the Nonlinear Autoregressive with eXogenous input (NARX) network, Gamma test, cross-validation, Bayesian regularization method and indicator kriging (IK). For practical application, this study investigated a heavily As-contaminated area in Taiwan. The backpropagation neural network (BPNN) is adopted for comparison purpose. The results demonstrate that the NARX network (Root mean square error (RMSE): 95.11 μg l-1 for training; 106.13 μg l-1 for validation) outperforms the BPNN (RMSE: 121.54 μg l-1 for training; 143.37 μg l-1 for validation). The constructed SDM can provide reliable estimation (R2 > 0.89) of As concentration at ungauged sites based merely on three easily-measured water quality variables (Alk, Ca2+ and pH). In addition, risk maps under the threshold of the WHO drinking water standard (10 μg l-1) are derived by the IK to visually display the spatial and temporal variation of the As concentration in the whole study area at different time spans. The proposed SDM can be practically applied with satisfaction to the regional estimation in study areas of interest and the estimation of missing, hazardous or costly data to facilitate water resources management.

Assessing Changes in Precipitation and Impacts on Groundwater in Southeastern Brazil using Regional Hydroclimate Reconstruction

NASA Astrophysics Data System (ADS)

Nunes, A.; Fernandes, M.; Silva, G. C., Jr.

2017-12-01

Aquifers can be key players in regional water resources. Precipitation infiltration is the most relevant process in recharging the aquifers. In that regard, understanding precipitation changes and impacts on the hydrological cycle helps in the assessment of groundwater availability from the aquifers. Regional modeling systems can provide precipitation, near-surface air temperature, together with soil moisture at different ground levels from coupled land-surface schemes. More accurate those variables are better the evaluation of the precipitation impact on the groundwater. Downscaling of global reanalysis very often employs regional modeling systems, in order to give more detailed information for impact assessment studies at regional scales. In particular, the regional modeling system, Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), might improve the accuracy of hydrometeorological variables in regions with spatial and temporal scarcity of in-situ observations. SRDAS combines assimilation of precipitation estimates from gauge-corrected satellite-based products with spectral nudging technique. The SRDAS hourly outputs provide monthly means of atmospheric and land-surface variables, including precipitation, used in the calculations of the hydrological budget terms. Results show the impact of changes in precipitation on groundwater in the aquifer located near the southeastern coastline of Brazil, through the assessment of the water-cycle terms, using a hydrological model during dry and rainy periods found in the 15-year numerical integration of SRDAS.

Wildland fire emissions, carbon, and climate: U.S. emissions inventories

Treesearch

Narasimhan K. Larkin; Sean M. Raffuse; Tara M. Strand

2014-01-01

Emissions from wildland fire are both highly variable and highly uncertain over a wide range of temporal and spatial scales. Wildland fire emissions change considerably due to fluctuations from year to year with overall fire season severity, from season to season as different regions pass in and out of wildfire and prescribed fire periods, and from day to day as...

A reference solar spectral irradiance for use in atmospheric modeling

NASA Technical Reports Server (NTRS)

1982-01-01

The present state of knowledge concerning the absolute magnitude and temporal variability of the solar spectral irradiance is outlined with emphasis on wavelengths relevant to the mesosphere and stratosphere. Reference spectra for the wavelength region 175 to 850 nm are presented including estimates for solar maximum and solar minimum conditions. Values for the Lyman alpha emission are given separately.

Temporal patterns in species flowering in Sky Islands of the Sonoran Desert ecoregion

Treesearch

Theresa M. Crimmins; Michael A. Crimmins; C. David Bertelsen

2013-01-01

Highly variable moisture conditions in the Sonoran Desert play a significant role in shaping the composition and phenology of plants in this water-limited region. The flowering patterns of plants of the Finger Rock trail, located in the Santa Catalina Mountains of southern Arizona, have been very carefully documented on approximately a weekly basis for nearly three...

Regional variability in sea ice melt in a changing Arctic

PubMed Central

Perovich, Donald K.; Richter-Menge, Jacqueline A.

2015-01-01

In recent years, the Arctic sea ice cover has undergone a precipitous decline in summer extent. The sea ice mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean ice equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to ice losses in the Beaufort Sea, due to decreases in ice concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal trends from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea ice cover. PMID:26032323

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content and uncertainties of the hydrologic and climate measurements. Assessment of spatial variations in the model parameters and predictions provides an improved understanding of how much of the hydrologic response to land use, climate, and other properties is unique to specific locations versus more universally observed across catchments of the SRB. This approach advances understanding of water cycle variability at any location throughout the stream network, as a function of both landscape characteristics (e.g., soils, vegetation, land use) and external forcings (e.g., precipitation quantity and frequency). These improvements in predictions of streamflow dynamics will advance the ability to predict spatial and temporal variability in key solutes, such as nutrients, and their delivery to the Chesapeake Bay.

Distributed modelling of water resources in the Lower Jordan River Basin - from present day variability to suitability for new water sources

NASA Astrophysics Data System (ADS)

Gunkel, Anne; Lange, Jens

2010-05-01

The Middle East is characterized by a high temporal and spatial variability of rainfall. As a result, water resources are not reliable and severe drought events are frequent, worsening the natural water scarcity. Single high magnitude events may dominate the water balance of entire seasons - a fact that is poorly represented in the assessments of available water resources that are normally based on long term averages. Therefore, a distributed hydrological model with a high temporal and spatial resolution is applied to the Lower Jordan River basin (LJRB). The focus is hereby to capture the variability of rainfall and to investigate how this signal is amplified in the hydrological cycle in this arid and semi arid environment. Rainfall variability is addressed through a volume scanning rainfall radar providing precipitation data with a resolution of 5 minutes for entire seasons that serves as input to a conceptual hydrological model. The raw radar data recorded by a C-Band system was pre-corrected by a multiple regression approach prior to regionalization to the LJRB, ground truthing with rainfall station data and conditional merging. Despite certain uncertainties, the data documents the accentuated rainfall variability in the entire LJRB. In order to include the full range of present rainfall variability, one average and two extreme seasons (wet and dry) are studied. Hydrological modelling is undertaken with a new modelling tool created by coupling two hydrological models, TRAIN and ZIN, complementing each other in respect to the addressed processes and water fluxes. The resulting modelling tool enables conceptual modelling of the processes relevant for semi-arid / arid environments with a high temporal and spatial resolution. The model is applied to the large scale LJRB (16,000 km²) in order to simulate all components of the water balance for three rainy seasons representing the present climate variability. Under given conditions of low data availability, the results give a basin wide view on the availability of surface water resources without human intervention with a high resolution in time (5 min) and space (up to 250 x 250 m²). The scarcity of water resources in many areas within the region is illustrated and detailed maps of the water balance components reveal spatial pattern of water availability characterizing the different potentials of regions or sub basins for water management options. Moreover, comparing different climate conditions provides valuable information for water management, including insights into the relation between green and blue water. For instance, runoff generation and percolation react stronger to changes in precipitation than evapotranspiration and the changes in runoff and percolation are considerably higher than the differences in rainfall between the three years. This amplification of rainfall variability by the hydrological cycle is significant for water management. Based on the results for current conditions, the impact of different scenarios and management options is analyzed, e.g. the effect of land use changes or the suitability of different regions for rainwater harvesting, one of the urgently needed new water sources.

Time variable eddy mixing in the global Sea Surface Salinity maxima

NASA Astrophysics Data System (ADS)

Busecke, J. J. M.; Abernathey, R.; Gordon, A. L.

2016-12-01

Lateral mixing by mesoscale eddies is widely recognized as a crucial mechanism for the global ocean circulation and the associated heat/salt/tracer transports. The Salinity in the Upper Ocean Processes Study (SPURS) confirmed the importance of eddy mixing for the surface salinity fields even in the center of the subtropical gyre of the North Atlantic. We focus on the global salinity maxima due to their role as indicators for global changes in the hydrological cycle as well as providing the source water masses for the shallow overturning circulation. We introduce a novel approach to estimate the contribution of eddy mixing to the global sea surface salinity maxima. Using a global 2D tracer experiments in a 1/10 degree MITgcm setup driven by observed surface velocities, we analyze the effect of eddy mixing using a water mass framework, thus focussing on the diffusive flux across surface isohalines. This enables us to diagnose temporal variability on seasonal to inter annual time scales, revealing regional differences in the mechanism causing temporal variability.Sensitivity experiments with various salinity backgrounds reveal robust inter annual variability caused by changes in the surface velocity fields potentially forced by large scale climate.

Interannual and seasonal variability in short-term grazing impact of Euphausia superba in nearshore and offshore waters west of the Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Ross, R. M.; Quetin, L. B.; Haberman, K. L.

1998-11-01

Our focus in this paper is the interaction between macrozooplanktonic grazers and primary producers, and the interannual and seasonal variability in the Palmer Long-Term Ecological Research (Palmer LTER) study region from Anvers Island to Adelaide Island. Short-term grazing estimates are calculated by integrating (1) theoretical and experimental estimates of ingestion rates in response to the standing stock of phytoplankton, and (2) field measurements of phytoplankton standing stock and grazer biomass. Field data come from three austral summer cruises (January/February of 1993, 1994, and 1995) and one sequence of seasonal cruises (summer, fall and winter 1993). The relative and absolute abundance of the dominant macrozooplankton grazers, Euphausia superba and Salpa thompsoni, varied by at least an order of magnitude on the spatial and temporal scales observed. Mean grazing rates ranged from 0.4 to 9.0 μg chlorophyll m -2 h -1 for the Antarctic krill and salp populations over the three summer cruises. This leads to variability in the flow of carbon from the primary producers through the grazers on the same scales. Temporal and spatial variability in grazing impact and faecal pellet production are high.

Cenozoic forearc tectonics in northeastern Japan: Relationships between outer forearc subsidence and plate boundary kinematics

NASA Astrophysics Data System (ADS)

Regalla, Christine

Here we investigate the relationships between outer forearc subsidence, the timing and kinematics of upper plate deformation and plate convergence rate in Northeast Japan to evaluate the role of plate boundary dynamics in driving forearc subsidence. The Northeastern Japan margin is one of the first non-accretionary subduction zones where regional forearc subsidence was argued to reflect tectonic erosion of large volumes of upper crustal rocks. However, we propose that a significant component of forearc subsidence could be the result of dynamic changes in plate boundary geometry. We provide new constraints on the timing and kinematics of deformation along inner forearc faults, new analyses of the evolution of outer forearc tectonic subsidence, and updated calculations of plate convergence rate. These data collectively reveal a temporal correlation between the onset of regional forearc subsidence, the initiation of upper plate extension, and an acceleration in local plate convergence rate. A similar analysis of the kinematic evolution of the Tonga, Izu-Bonin, and Mariana subduction zones indicates that the temporal correlations observed in Japan are also characteristic of these three non-accretionary margins. Comparison of these data with published geodynamic models suggests that forearc subsidence is the result of temporal variability in slab geometry due to changes in slab buoyancy and plate convergence rate. These observations suggest that a significant component of forearc subsidence at these four margins is not the product of tectonic erosion, but instead reflects changes in plate boundary dynamics driven by variable plate kinematics.

Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy.

PubMed

Lambon Ralph, Matthew A; Ehsan, Sheeba; Baker, Gus A; Rogers, Timothy T

2012-01-01

Contemporary clinical and basic neuroscience studies have increasingly implicated the anterior temporal lobe regions, bilaterally, in the formation of coherent concepts. Mounting convergent evidence for the importance of the anterior temporal lobe in semantic memory is found in patients with bilateral anterior temporal lobe damage (e.g. semantic dementia), functional neuroimaging and repetitive transcranial magnetic stimulation studies. If this proposal is correct, then one might expect patients with anterior temporal lobe resection for long-standing temporal lobe epilepsy to be semantically impaired. Such patients, however, do not present clinically with striking comprehension deficits but with amnesia and variable anomia, leading some to conclude that semantic memory is intact in resection for temporal lobe epilepsy and thus casting doubt over the conclusions drawn from semantic dementia and linked basic neuroscience studies. Whilst there is a considerable neuropsychological literature on temporal lobe epilepsy, few studies have probed semantic memory directly, with mixed results, and none have undertaken the same type of systematic investigation of semantic processing that has been conducted with other patient groups. In this study, therefore, we investigated the semantic performance of 20 patients with resection for chronic temporal lobe epilepsy with a full battery of semantic assessments, including more sensitive measures of semantic processing. The results provide a bridge between the current clinical observations about resection for temporal lobe epilepsy and the expectations from semantic dementia and other neuroscience findings. Specifically, we found that on simple semantic tasks, the patients' accuracy fell in the normal range, with the exception that some patients with left resection for temporal lobe epilepsy had measurable anomia. Once the semantic assessments were made more challenging, by probing specific-level concepts, lower frequency/more abstract items or measuring reaction times on semantic tasks versus those on difficulty-matched non-semantic assessments, evidence of a semantic impairment was found in all individuals. We conclude by describing a unified, computationally inspired framework for capturing the variable degrees of semantic impairment found across different patient groups (semantic dementia, temporal lobe epilepsy, glioma and stroke) as well as semantic processing in neurologically intact participants.

Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy

PubMed Central

Ehsan, Sheeba; Baker, Gus A.; Rogers, Timothy T.

2012-01-01

Contemporary clinical and basic neuroscience studies have increasingly implicated the anterior temporal lobe regions, bilaterally, in the formation of coherent concepts. Mounting convergent evidence for the importance of the anterior temporal lobe in semantic memory is found in patients with bilateral anterior temporal lobe damage (e.g. semantic dementia), functional neuroimaging and repetitive transcranial magnetic stimulation studies. If this proposal is correct, then one might expect patients with anterior temporal lobe resection for long-standing temporal lobe epilepsy to be semantically impaired. Such patients, however, do not present clinically with striking comprehension deficits but with amnesia and variable anomia, leading some to conclude that semantic memory is intact in resection for temporal lobe epilepsy and thus casting doubt over the conclusions drawn from semantic dementia and linked basic neuroscience studies. Whilst there is a considerable neuropsychological literature on temporal lobe epilepsy, few studies have probed semantic memory directly, with mixed results, and none have undertaken the same type of systematic investigation of semantic processing that has been conducted with other patient groups. In this study, therefore, we investigated the semantic performance of 20 patients with resection for chronic temporal lobe epilepsy with a full battery of semantic assessments, including more sensitive measures of semantic processing. The results provide a bridge between the current clinical observations about resection for temporal lobe epilepsy and the expectations from semantic dementia and other neuroscience findings. Specifically, we found that on simple semantic tasks, the patients’ accuracy fell in the normal range, with the exception that some patients with left resection for temporal lobe epilepsy had measurable anomia. Once the semantic assessments were made more challenging, by probing specific-level concepts, lower frequency/more abstract items or measuring reaction times on semantic tasks versus those on difficulty-matched non-semantic assessments, evidence of a semantic impairment was found in all individuals. We conclude by describing a unified, computationally inspired framework for capturing the variable degrees of semantic impairment found across different patient groups (semantic dementia, temporal lobe epilepsy, glioma and stroke) as well as semantic processing in neurologically intact participants. PMID:22287382

Estimates of spatially and temporally resolved constrained black carbon emission over the Indian region using a strategic integrated modelling approach

NASA Astrophysics Data System (ADS)

Verma, S.; Reddy, D. Manigopal; Ghosh, S.; Kumar, D. Bharath; Chowdhury, A. Kundu

2017-10-01

We estimated the latest spatially and temporally resolved gridded constrained black carbon (BC) emissions over the Indian region using a strategic integrated modelling approach. This was done extracting information on initial bottom-up emissions and atmospheric BC concentration from a general circulation model (GCM) simulation in conjunction with the receptor modelling approach. Monthly BC emission (83-364 Gg) obtained from the present study exhibited a spatial and temporal variability with this being the highest (lowest) during February (July). Monthly BC emission flux was considerably high (> 100 kg km- 2) over the entire Indo-Gangetic plain (IGP), east and the west coast during winter months. This was relatively higher over the central and western India than over the IGP during summer months. Annual BC emission rate was 2534 Gg y- 1 with that over the IGP and central India respectively comprising 50% and 40% of the total annual BC emissions over India. A high relative increase was observed in modified BC emissions (more than five times the initial emissions) over the most part of the IGP, east coast, central/northwestern India. The relative predominance of monthly BC emission flux over a region (as depicted from z-score distribution maps) was inferred being consistent with the prevalence of region- and season-specific anthropogenic activity.

Factors affecting temporal variability of arsenic in groundwater used for drinking water supply in the United States

USGS Publications Warehouse

Ayotte, Joseph D.; Belaval, Marcel; Olson, Scott A.; Burow, Karen R.; Flanagan, Sarah M.; Hinkle, Stephen R.; Lindsey, Bruce D.

2014-01-01

The occurrence of arsenic in groundwater is a recognized environmental hazard with worldwide importance and much effort has been focused on surveying and predicting where arsenic occurs. Temporal variability is one aspect of this environmental hazard that has until recently received less attention than other aspects. For this study, we analyzed 1245 wells with two samples per well. We suggest that temporal variability, often reported as affecting very few wells, is perhaps a larger issue than it appears and has been masked by datasets with large numbers of non-detect data. Although there was only a slight difference in arsenic concentration variability among samples from public and private wells (p = 0.0452), the range of variability was larger for public than for private wells. Further, we relate the variability we see to geochemical factors—primarily variability in redox—but also variability in pH and major-ion chemistry. We also show that in New England there is a weak but statistically significant indication that seasonality may have an effect on concentrations, whereby concentrations in the first two quarters of the year (January–June) are significantly lower than in the second two quarters (July–December) (p < 0.0001). In the Central Valley of California, though not statistically significant (p = 0.4169), arsenic concentration is lower in the first quarter of the year but increases in subsequent quarters. In both regions, these changes appear to follow groundwater levels. It is possible that this difference in arsenic concentrations is related to groundwater level changes, pumping stresses, evapotranspiration effects, or perhaps mixing of more oxidizing, lower pH recharge water in wetter months. Focusing on the understanding the geochemical conditions in aquifers where arsenic concentrations are concerns and causes of geochemical changes in the groundwater environment may lead to a better understanding of where and by how much arsenic will vary over time.

Marine reservoir age variability and water mass distribution in the Iceland Sea

NASA Astrophysics Data System (ADS)

Eiríksson, Jón; Larsen, Gudrún; Knudsen, Karen Luise; Heinemeier, Jan; Símonarson, Leifur A.

2004-11-01

Lateglacial and Holocene tephra markers from Icelandic source volcanoes have been identified in five sediment cores from the North Icelandic shelf and correlated with tephra layers in reference soil sections in North Iceland and the GRIP ice core. Land-sea correlation of tephra markers, that have been radiocarbon dated with terrestrial material or dated by documentary evidence, provides a tool for monitoring reservoir age variability in the region. Age models developed for the shelf sediments north of Iceland, based on offshore tephrochronology on one hand and on calibrated AMS 14C datings of marine molluscs on the other, display major deviations during the last 4500 years. The inferred temporal variability in the reservoir age of the regional water masses exceeds by far the variability expected from the marine model calculations. The observed reservoir ages are generally considerably higher, by up to 450 years, than the standard model ocean. It is postulated that the intervals with increased and variable marine reservoir age reflect incursions of Arctic water masses derived from the East Greenland Current to the Iceland Sea and the North Icelandic shelf.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Observed Temporal and Spatial Variability in the Marine Environment at the Sub-Antarctic Prince Edward Islands - Evidence of a Changing Climate?

NASA Astrophysics Data System (ADS)

Asdar, S.; Deshayes, J.; Ansorge, I. J.

2016-02-01

The sub-Antarctic Prince Edward Islands (PEI) (47°S,38°E) are classified as isolated, hostile, impoverished regions, in which the terrestrial and marine ecosystems are relatively simple and extremely sensitive to perturbations. Their location between the Sub-Antarctic Front (SAF) and the Antarctic Polar Front (APF), bordering the Antarctic Circumpolar Current (ACC) provides an ideal natural laboratory for studying how organisms, ecological processes and ecosystems respond to a changing ocean climate in the Southern Ocean. Recent studies have proposed that climate changes reported at the PEI may correspond in time to a southward shift of the ACC and in particular of the SAF. This southward migration in the geographic position is likely to coincide with dramatic changes in the distribution of species and total productivity of this region. This study focuses on the inter-comparison of observations available at these islands. Using spectral analysis which is a study of the frequency domain characteristics of a process, we first determine the dominant characteristics of both the temporal and spatial variability of physical and biogeochemical properties. In doing so the authors are able to determine whether and how these indices of variability interact with one another in order to understand better the mechanisms underpinning this variability, i.e. the seasonal zonal migrations associated with the SAF. Additionally, we include in our analysis recent data from 2 ADCP moorings deployed between the islands from 2014 to 2015. These in-situ observations of circulation and hydrography in the vicinity of the islands provide a unique opportunity to establish a better understanding of how large scale climatic variability may impact local conditions, and more importantly its influence on the fragile ecosystem surrounding the PEI.

Chromophoric Dissolved Organic Matter across a Marine Distributed Biological Observatory in the Pacific Arctic Region

NASA Astrophysics Data System (ADS)

Berman, S. L.; Frey, K. E.; Shake, K. L.; Cooper, L. W.; Grebmeier, J. M.

2014-12-01

Dissolved organic matter (DOM) plays an important role in marine ecosystems as both a carbon source for the microbial food web (and thus a source of CO2 to the atmosphere) and as a light inhibitor in marine environments. The presence of chromophoric dissolved organic matter (CDOM; the optically active portion of total DOM) can have significant controlling effects on transmittance of sunlight through the water column and therefore on primary production as well as the heat balance of the upper ocean. However, CDOM is also susceptible to photochemical degradation, which decreases the flux of solar radiation that is absorbed. Knowledge of the current spatial and temporal distribution of CDOM in marine environments is thus critical for understanding how ongoing and future changes in climate may impact these biological, biogeochemical, and physical processes. We describe the quantity and quality of CDOM along five key productive transects across a developing Distributed Biological Observatory (DBO) in the Pacific Arctic region. The samples were collected onboard the CCGS Sir Wilfred Laurier in July 2013 and 2014. Monitoring of the variability of CDOM along transects of high productivity can provide important insights into biological and biogeochemical cycling across the region. Our analyses include overall concentrations of CDOM, as well as proxy information such as molecular weight, lability, and source (i.e., autochthonous vs. allochthonous) of organic matter. We utilize these field observations to compare with satellite-derived CDOM concentrations determined from the Aqua MODIS satellite platform, which ultimately provides a spatially and temporally continuous synoptic view of CDOM concentrations throughout the region. Examining the current relationships among CDOM, sea ice variability, biological productivity, and biogeochemical cycling in the Pacific Arctic region will likely provide key insights for how ecosystems throughout the region will respond in future scenarios of climate change.

Accounting for inter-annual and seasonal variability in regionalization of hydrologic response in the Great Lakes basin

NASA Astrophysics Data System (ADS)

Kult, J. M.; Fry, L. M.; Gronewold, A. D.

2012-12-01

Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response typically invoke the concept of regionalization, whereby knowledge pertaining to gauged catchments is transferred to ungauged catchments. In this study, we identify watershed physical characteristics acting as primary drivers of hydrologic response throughout the US portion of the Great Lakes basin. Relationships between watershed physical characteristics and hydrologic response are generated from 166 catchments spanning a variety of climate, soil, land cover, and land form regimes through regression tree analysis, leading to a grouping of watersheds exhibiting similar hydrologic response characteristics. These groupings are then used to predict response in ungauged watersheds in an uncertainty framework. Results from this method are assessed alongside one historical regionalization approach which, while simple, has served as a cornerstone of Great Lakes regional hydrologic research for several decades. Our approach expands upon previous research by considering multiple temporal characterizations of hydrologic response. Due to the substantial inter-annual and seasonal variability in hydrologic response observed over the Great Lakes basin, results from the regression tree analysis differ considerably depending on the level of temporal aggregation used to define the response. Specifically, higher levels of temporal aggregation for the response metric (for example, indices derived from long-term means of climate and streamflow observations) lead to improved watershed groupings with lower within-group variance. However, this perceived improvement in model skill occurs at the cost of understated uncertainty when applying the regression to time series simulations or as a basis for model calibration. In such cases, our results indicate that predictions based on long-term characterizations of hydrologic response can produce misleading conclusions when applied at shorter time steps. This study suggests that measures of hydrologic response quantified at these shorter time steps may provide a more robust basis for making predictions in applications of water resource management, model calibration and simulations, and human health and safety.

[The variability of vegetation beginning date of greenness period in spring in the north-south transect of eastern China based on NOAA NDVI].

PubMed

Wang, Zhi; Liu, Shi-rong; Sun, Peng-sen; Guo, Zhi-hua; Zhou, Lian-di

2010-10-01

NDVI based on NOAA/AVHRR from 1982 to 2003 are used to monitor variable rules for the growing season in spring of vegetation in the north-south transect of eastern China (NSTEC). The following, mainly, are included: (1) The changing speed of greenness period in spring of most regions in NSTEC is slow and correlation with the year is not distinct; (2) The regions in which greenness period in spring distinctly change mainly presented an advance; (3) The regions in which inter-annual fluctuation of greenness period in spring is over 10 days were found in 3 kinds of areas: the area covered with agricultural vegetation types; the areas covered with evergreen vegetation types; the areas covered with steppe vegetation types; (4) changes of vegetation greenness period in spring have spatio-temporal patterns.

Spatial and temporal variability in response to hybrid electro-optical stimulation

NASA Astrophysics Data System (ADS)

Duke, Austin R.; Lu, Hui; Jenkins, Michael W.; Chiel, Hillel J.; Jansen, E. Duco

2012-06-01

Hybrid electro-optical neural stimulation is a novel paradigm combining the advantages of optical and electrical stimulation techniques while reducing their respective limitations. However, in order to fulfill its promise, this technique requires reduced variability and improved reproducibility. Here we used a comparative physiological approach to aid the further development of this technique by identifying the spatial and temporal factors characteristic of hybrid stimulation that may contribute to experimental variability and/or a lack of reproducibility. Using transient pulses of infrared light delivered simultaneously with a bipolar electrical stimulus in either the marine mollusk Aplysia californica buccal nerve or the rat sciatic nerve, we determined the existence of a finite region of excitability with size altered by the strength of the optical stimulus and recruitment dictated by the polarity of the electrical stimulus. Hybrid stimulation radiant exposures yielding 50% probability of firing (RE50) were shown to be negatively correlated with the underlying changes in electrical stimulation threshold over time. In Aplysia, but not in the rat sciatic nerve, increasing optical radiant exposures (J cm-2) beyond the RE50 ultimately resulted in inhibition of evoked potentials. Accounting for the sources of variability identified in this study increased the reproducibility of stimulation from 35% to 93% in Aplysia and 23% to 76% in the rat with reduced variability.

New spatial and temporal indices of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Dwivedi, Sanjeev; Uma, R.; Lakshmi Kumar, T. V.; Narayanan, M. S.; Pokhrel, Samir; Kripalani, R. H.

2018-02-01

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Temporal analysis of regional wall motion from cine cardiac MRI

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Didier, Dominique; Chretien, Anne; Rosset, Antoine; Magnin, Isabelle E.; Ligier, Yves

1996-04-01

The purpose of this work is to develop and to evaluate an automatic analysis technique for quantitative assessment of cardiac function from cine MRI and to identify regional alterations in synchronicity based on Fourier analysis of ventricular wall motion (WM). A temporal analysis technique of left ventricular wall displacement was developed for quantitative analysis of temporal delays in wall motion and applied to gated cine 'dark blood' cardiac MRI. This imaging technique allows the user to saturate the blood both above and below the imaging slice simultaneously by using a specially designed rf presaturation pulse. The acquisition parameters are: TR equals 25 - 60 msec, TE equals 5 - 7 msec, 0 equals 25 degrees, slice thickness equals 10 mm, 16 to 32 frames/cycle. Automatic edge detection was used to outline the ventricular cavities on all frames of a cardiac cycle. Two different segmentation techniques were applied to all studies and lead to similar results. Further improvement in edge detection accuracy was achieved by temporal interpolation of individual contours on each image of the cardiac cycle. Radial analysis of the ventricular wall motion was then performed along 64 radii drawn from the center of the ventricular cavity. The first harmonic of the Fourier transform of each radial motion curve is calculated. The phase of the fundamental Fourier component is used as an index of synchrony (delay) of regional wall motion. Results are displayed in color-coded maps of regional alterations in the amplitude and synchrony of wall motion. The temporal delays measured from individual segments are evaluated through a histogram of phase distribution, where the width of the main peak is used as an index of overall synchrony of wall motion. The variability of this technique was validated in 10 normal volunteers and was used to identify regions with asynchronous WM in 15 patients with documented CAD. The standard deviation (SD) of phase distribution measured in short axis views was calculated and used to identify regions with asynchronous wall motion in patients with coronary artery disease. Results suggest that this technique is more sensitive than global functional parameters such as ejection fraction for the detection of ventricular dysfunction. Color coded parametric display offers a more convenient way for the identification and localization of regional wall motion asynchrony. Data obtained from endocardial wall motion analysis were not significantly different from wall thickening measurements. The innovative approach of evaluating the temporal behavior of regional wall motion anomalies is expected to provide clinically relevant data about subtle alteration that cannot be detected through simple analysis of the extent (amplitude) of wall motion or myocardial thickening. Temporal analysis of regional WM abnormality from cine MRI offers an innovative and promising means for objective quantitative evaluation of subtle regional abnormalities. Color coded parametric maps allowed a better identification and localization of regional WM asynchrony.

Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales

USGS Publications Warehouse

Angeler, David G.; Allen, Criag R.; Johnson, Richard K.

2012-01-01

Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.

Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980-2010

NASA Astrophysics Data System (ADS)

Gummadi, Sridhar; Rao, K. P. C.; Seid, Jemal; Legesse, Gizachew; Kadiyala, M. D. M.; Takele, Robel; Amede, Tilahun; Whitbread, Anthony

2017-12-01

This article summarizes the results from an analysis conducted to investigate the spatio-temporal variability and trends in the rainfall over Ethiopia over a period of 31 years from 1980 to 2010. The data is mostly observed station data supplemented by bias-corrected AgMERRA climate data. Changes in annual and Belg (March-May) and Kiremt (June to September) season rainfalls and rainy days have been analysed over the entire Ethiopia. Rainfall is characterized by high temporal variability with coefficient of variation (CV, %) varying from 9 to 30% in the annual, 9 to 69% during the Kiremt season and 15-55% during the Belg season rainfall amounts. Rainfall variability increased disproportionately as the amount of rainfall declined from 700 to 100 mm or less. No significant trend was observed in the annual rainfall amounts over the country, but increasing and decreasing trends were observed in the seasonal rainfall amounts in some areas. A declining trend is also observed in the number of rainy days especially in Oromia, Benishangul-Gumuz and Gambella regions. Trends in seasonal rainfall indicated a general decline in the Belg season and an increase in the Kiremt season rainfall amounts. The increase in rainfall during the main Kiremt season along with the decrease in the number of rainy days leads to an increase in extreme rainfall events over Ethiopia. The trends in the 95th-percentile rainfall events illustrate that the annual extreme rainfall events are increasing over the eastern and south-western parts of Ethiopia covering Oromia and Benishangul-Gumuz regions. During the Belg season, extreme rainfall events are mostly observed over central Ethiopia extending towards the southern part of the country while during the Kiremt season, they are observed over parts of Oromia, (covering Borena, Guji, Bali, west Harerge and east Harerge), Somali, Gambella, southern Tigray and Afar regions. Changes in the intensity of extreme rainfall events are mostly observed over south-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

An assessment of temporal effect on extreme rainfall estimates

NASA Astrophysics Data System (ADS)

Das, Samiran; Zhu, Dehua; Chi-Han, Cheng

2018-06-01

This study assesses the temporal behaviour in terms of inter-decadal variability of extreme daily rainfall of stated return period relevant for hydrologic risk analysis using a novel regional parametric approach. The assessment is carried out based on annual maximum daily rainfall series of 180 meteorological stations of Yangtze River Basin over a 50-year period (1961-2010). The outcomes of the analysis reveal that while there were effects present indicating higher quantile values when estimated from data of the 1990s, it is found not to be noteworthy to exclude the data of any decade from the extreme rainfall estimation process for hydrologic risk analysis.

1996-2007 Interannual Spatio-Temporal Variability in Snowmelt in Two Montane Watersheds

NASA Astrophysics Data System (ADS)

Jepsen, S. M.; Molotch, N. P.; Williams, M. W.; Rittger, K. E.; Sickman, J. O.

2010-12-01

Snowmelt is a primary water resource for urban/agricultural centers and ecosystems near mountain regions. Stream chemistry from montane catchments is controlled by the flowpaths of water from snowmelt and the timing and duration of snow coverage. A process level understanding of the variability in these processes requires an understanding of the effect of changing climate and anthropogenic loading on spatio-temporal snowmelt patterns. With this as our objective, we applied a snow reconstruction model (SRM) to two well-studied montane watersheds, Tokopah Basin (TOK), California and Green Lake 4 Valley (GLV), Colorado, to examine interannual variability in the timing and location of snowmelt in response to variable climate conditions during the period from 1996 to 2007. The reconstruction model back solves for snowmelt by combining surface energy fluxes, inferred from meteorological data, with sequences of melt season snow images derived from satellite data (i.e., snowmelt depletion curves). The SRM explained 84% of the observed interannual variability in maximum watershed SWE in TOK, with errors ranging from -23 to +27% for the different years. For GLV4, the SRM explained 61% of the interannual variability, with errors ranging from -37 to +34%. In GLV4, interannual variability in snowmelt timing is a factor of four greater than the variability in streamflow timing, unlike in TOK where the ratio is nearly 1:1. We attribute this difference primarily to differences in the magnitude of the turbulent fluxes and the hydrogeology of the two study areas.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Community temporal variability increases with fluctuating resource availability

PubMed Central

Li, Wei; Stevens, M. Henry H.

2017-01-01

An increase in the quantity of available resources is known to affect temporal variability of aggregate community properties. However, it is unclear how might fluctuations in resource availability alter community-level temporal variability. Here we conduct a microcosm experiment with laboratory protist community subjected to manipulated resource pulses that vary in intensity, duration and time of supply, and examine the impact of fluctuating resource availability on temporal variability of the recipient community. The results showed that the temporal variation of total protist abundance increased with the magnitude of resource pulses, as protist community receiving infrequent resource pulses (i.e., high-magnitude nutrients per pulse) was relatively more unstable than community receiving multiple resource pulses (i.e., low-magnitude nutrients per pulse), although the same total amounts of nutrients were added to each community. Meanwhile, the timing effect of fluctuating resources did not significantly alter community temporal variability. Further analysis showed that fluctuating resource availability increased community temporal variability by increasing the degree of community-wide species synchrony and decreasing the stabilizing effects of dominant species. Hence, the importance of fluctuating resource availability in influencing community stability and the regulatory mechanisms merit more attention, especially when global ecosystems are experiencing high rates of anthropogenic nutrient inputs. PMID:28345592

Community temporal variability increases with fluctuating resource availability

NASA Astrophysics Data System (ADS)

Li, Wei; Stevens, M. Henry H.

2017-03-01

An increase in the quantity of available resources is known to affect temporal variability of aggregate community properties. However, it is unclear how might fluctuations in resource availability alter community-level temporal variability. Here we conduct a microcosm experiment with laboratory protist community subjected to manipulated resource pulses that vary in intensity, duration and time of supply, and examine the impact of fluctuating resource availability on temporal variability of the recipient community. The results showed that the temporal variation of total protist abundance increased with the magnitude of resource pulses, as protist community receiving infrequent resource pulses (i.e., high-magnitude nutrients per pulse) was relatively more unstable than community receiving multiple resource pulses (i.e., low-magnitude nutrients per pulse), although the same total amounts of nutrients were added to each community. Meanwhile, the timing effect of fluctuating resources did not significantly alter community temporal variability. Further analysis showed that fluctuating resource availability increased community temporal variability by increasing the degree of community-wide species synchrony and decreasing the stabilizing effects of dominant species. Hence, the importance of fluctuating resource availability in influencing community stability and the regulatory mechanisms merit more attention, especially when global ecosystems are experiencing high rates of anthropogenic nutrient inputs.

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

A national perspective on paleoclimate streamflow and water storage infrastructure in the conterminous United States

NASA Astrophysics Data System (ADS)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward

2017-04-01

Large-scale water storage infrastructure in the Conterminous United States (CONUS) provides a means of regulating the temporal variability in water supply with storage capacities ranging from seasonal storage in the wetter east to multi-annual and decadal-scale storage in the drier west. Regional differences in water availability across the CONUS provides opportunities for optimizing water dependent economic activities, such as food and energy production, through storage and transportation. However, the ability to sufficiently regulate water supplies into the future is compromised by inadequate monitoring of non-federally-owned dams that make up around 97% of all dams. Furthermore, many of these dams are reaching or have exceeded their economic design life. Understanding the role of dams in the current and future landscape of water requirements in the CONUS is needed to prioritize dam safety remediation or identify where redundant dams may be removed. A national water assessment and planning process is needed for addressing water requirements, accounting for regional differences in water supply and demand, and the role of dams in such a landscape. Most dams in the CONUS were designed without knowledge of devastating floods and prolonged droughts detected in multi-centennial paleoclimate records, consideration of projected climate change, nor consideration of optimal operation across large-scale regions. As a step towards informing water supply across the CONUS we present a paleoclimate reconstruction of annual streamflow across the CONUS over the past 555 years using a spatially and temporally complete paleoclimate record of summer drought across the CONUS targeting a set of US Geological Survey streamflow sites. The spatial and temporal structures of national streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s) and 1950s droughts. Decadal-scale variability was detected in the late 1900s in the western US, however, similar modes of temporal variability were rarely present prior to the 1950s. The 20th century featured longer wet spells and shorter dry spells compared with the preceding 450 years. Streamflow in the Pacific Northwest and Northeast are negatively correlated with the central US suggesting the potential to mitigate some drought impacts by balancing economic activities and insurance pools across these regions during major droughts. The converging issues of a slowly growing US population, evolving demands for food, energy, and water, aging dams, and reduced water storage capacity through decommissioning and sedimentation highlights the pressing need for a national water assessment and a subsequent national water plan. There are many factors that need to be understood in order to appropriately assess dam and reservoir requirements across the CONUS and to improve water use and flood protection efficiency. In addition to historical and paleoclimate-informed surface water supply, factors requiring consideration in planning for future dam and reservoir infrastructure include: -the role of conjunctive surface and groundwater storage and use; -basin-scale operational strategies to balance sectoral water demand; -projections of surface water supply; -projections of regional water demands; -impacts of water conservation; and -the influence of water policy and financial instruments.

Multi-sensor Oceanographic Correlations for Pacific Hake Acoustic Survey Improvement

NASA Astrophysics Data System (ADS)

Brozen, M.; Hillyer, N.; Holt, B.; Armstrong, E. M.

2010-12-01

North Pacific hake (Merluccius productus), the most abundant groundfish along the Pacific coast of northwestern America, are an essential source of income for the coastal region from southern California to British Columbia, Canada. However, hake abundance and distribution are highly variable among years, exhibiting variance in both the north-south and east-west distribution as seen in the results from biannual acoustic surveys. This project is part of a larger undertaking, ultimately focused on the prediction of hake distribution to improve the distribution of survey effort and precision of stock assessments in the future. Four remotely sensed oceanographic variables are examined as a first step in improving our understanding the relationship between the intensity of coastal upwelling and other ocean dynamics, and the north-south summer hake distribution. Sea surface height, wind vectors, chlorophyll - a concentrations, and sea surface temperature were acquired from several satellites, including AVHRR, SeaWifs, TOPEX/Poseidon, Jason-1, Jason-2, SSM/I, ASMR-E, and QuikScat. Data were aligned to the same spatial and temporal resolution, and these re-gridded data were then analyzed using empirical orthogonal functions (EOFs). EOFs were used as a spatio-temporally compact representation of the data and to reduce the co-variability of the multiple time series in the dataset. The EOF results were plotted and acoustic survey results were overlaid to understand differences between regions. Although this pilot project used data from only a single year (2007), it demonstrated a methodology for reducing dimensionality of linearly related satellite variables that can used in future applications, and provided insight into multi-dimensional ocean characteristics important for hake distribution.

Spatio-Temporal Variability of Urban Heat Island and Urban Mobility

NASA Astrophysics Data System (ADS)

Kar, B.; Omitaomu, O.

2017-12-01

A 2016 report by the U.S. Census stated that while the rural areas cover 97% of the U.S. landmass, these areas house only 19.7% of the nation's population. Given that the U.S. coastal counties are home to more than 50% of the U.S. population, these urban areas are clustered along the coast that is susceptible to sea level rise induced impacts. In light of increasing climate variability and extreme events, it is pertinent to understand the Urban Heat Island (UHI) effect that results from increasing population density and mobility in the urban areas, and that contributes to increased energy consumption and temperature as well as unmitigated flooding events. For example, in Illinois, warmer summers contribute to heavy precipitation that overwhelms the region's drainage capacity. This study focuses on understanding the spatio-temporal variability of the relationship between population density and mobility distribution, and creation of UHI due to temperature change in selected cities across the U.S. This knowledge will help us understand the role of UHI in energy-water nexus in urban areas, specifically, energy consumption.

Modelling larval dispersal dynamics of common sole (Solea solea) along the western Iberian coast

NASA Astrophysics Data System (ADS)

Tanner, Susanne E.; Teles-Machado, Ana; Martinho, Filipe; Peliz, Álvaro; Cabral, Henrique N.

2017-08-01

Individual-based coupled physical-biological models have become the standard tool for studying ichthyoplankton dynamics and assessing fish recruitment. Here, common sole (Solea solea L.), a flatfish of high commercial importance in Europe was used to evaluate transport of eggs and larvae and investigate the connectivity between spawning and nursery areas along the western Iberian coast as spatio-temporal variability in dispersal and recruitment patterns can result in very strong or weak year-classes causing large fluctuations in stock size. A three-dimensional particle tracking model coupled to Regional Ocean Modelling System model was used to investigate variability of sole larvae dispersal along the western Iberian coast over a five-year period (2004-2009). A sensitivity analysis evaluating: (1) the importance of diel vertical migrations of larvae and (2) the size of designated recruitment areas was performed. Results suggested that connectivity patterns of sole larvae dispersal and their spatio-temporal variability are influenced by the configuration of the coast with its topographical structures and thus the suitable recruitment area available as well as the wind-driven mesoscale circulation along the Iberian coast.

Regions of pollution with particulate matter in Poland

NASA Astrophysics Data System (ADS)

Rawicki, Kacper; Czarnecka, Małgorzata; Nidzgorska-Lencewicz, Jadwiga

2018-01-01

The study presents the temporal and spatial variability of particulate matter concentration in Poland in the calendar winter season (December-February). The basis for the study were the hourly and daily values of particulate matter PM10 concentration from the period 2005/06 - 2014/15, obtained from 33 air pollution monitoring stations. In Poland, the obligation to monitor the concentration of the finer fraction of particles smaller than 2.5µm in aerodynamic diameter was introduced only in 2010. Consequently, data on PM2.5 concentration refer to a shorter period, i.e. 2009/10 - 2014/15, and were obtained from 23 stations. Using the cluster analysis (k-means method), three regions of comparable variability of particulate matter concentration were delineated. The largest region, i.e. Region I, comprises the northern and eastern central area of Poland, and its southern boundary is along the line Gorzów Wlkp-Bydgoszcz-Konin-Łódź-Kielce-Lublin. Markedly smaller Region II is located to the south of Region I. By far the smallest area was designated to Region III which covers the south west area of Poland. The delineated regions show a marked variability in terms of mean concentration of both PM fractions in winter (PM10: region I - 33 µg·m-3, region II - 55 µg·m-3, region III - 83 µg·m-3; PM2,5: region I - 35 µg·m-3, region II - 50 µg·m-3, region III - 60 µg·m-3) and, in the case of PM10, the frequency of excessive daily limit value.

Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

NASA Astrophysics Data System (ADS)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological stations. The proposed model will be validated by using the (National Centers for Environmental Prediction / National Center for Atmospheric Research) NCEP/NCAR predictors for the period of 1960-1990 and validated for 1990-2000. To investigate the efficiency of the proposed model, it will be compared with the multivariate multiple regression model and with dynamical downscaling climate models by using different climate indices that describe the frequency, intensity and duration of the variables of interest. KEY WORDS: Climate change, Copula, Monsoon, Quantile regression, Spatio-temporal distribution.

An integrated approach for estimation of methane emissions from wetlands and lakes in high latitude regions

NASA Astrophysics Data System (ADS)

Chiu, C.; Bowling, L. C.; Podest, E.; Bohn, T. J.; Lettenmaier, D. P.; Schroeder, R.; McDonald, K. C.

2009-04-01

In recent years, there has been increasing evidence of significant alteration in the extent of lakes and wetlands in high latitude regions due in part to thawing permafrost, as well as other changes governing surface and subsurface hydrology. Methane is a 23 times more efficient greenhouse gas than carbon dioxide; changes in surface water extent, and the associated subsurface anaerobic conditions, are important controls on methane emissions in high latitude regions. Methane emissions from wetlands vary substantially in both time and space, and are influenced by plant growth, soil organic matter decomposition, methanogenesis, and methane oxidation controlled by soil temperature, water table level and net primary productivity (NPP). The understanding of spatial and temporal heterogeneity of surface saturation, thermal regime and carbon substrate in northern Eurasian wetlands from point measurements are limited. In order to better estimate the magnitude and variability of methane emissions from northern lakes and wetlands, we present an integrated assessment approach based on remote sensing image classification, land surface modeling and process-based ecosystem modeling. Wetlands classifications based on L-band JERS-1 SAR (100m) and ALOS PALSAR (~30m) are used together with topographic information to parameterize a lake and wetland algorithm in the Variable Infiltration Capacity (VIC) land surface model at 25 km resolution. The enhanced VIC algorithm allows subsurface moisture exchange between surface water and wetlands and includes a sub-grid parameterization of water table position within the wetland area using a generalized topographic index. Average methane emissions are simulated by using the Walter and Heimann methane emission model based on temporally and spatially varying soil temperature, net primary productivity and water table generated from the modified VIC model. Our five preliminary study areas include the Z. Dvina, Upper Volga, Yeloguy, Syum, and Chaya river basins. The temporally-variable inundation extent simulated by the VIC model is compared to 25 km resolution inundation products developed from combined QuikSCAT, AMSR-E and MODIS data sets covering the time period from 2002 onward. The seasonal variation in methane emissions associated with sub-grid variability in water table extent is explored between 1948 and 2006. This work was carried out at Purdue University, at the University of Washington, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the NASA.

The relationship between species richness and ecosystem variability is shaped by the mechanism of coexistence.

PubMed

Tredennick, Andrew T; Adler, Peter B; Adler, Frederick R

2017-08-01

Theory relating species richness to ecosystem variability typically ignores the potential for environmental variability to promote species coexistence. Failure to account for fluctuation-dependent coexistence may explain deviations from the expected negative diversity-ecosystem variability relationship, and limits our ability to predict the consequences of increases in environmental variability. We use a consumer-resource model to explore how coexistence via the temporal storage effect and relative nonlinearity affects ecosystem variability. We show that a positive, rather than negative, diversity-ecosystem variability relationship is possible when ecosystem function is sampled across a natural gradient in environmental variability and diversity. We also show how fluctuation-dependent coexistence can buffer ecosystem functioning against increasing environmental variability by promoting species richness and portfolio effects. Our work provides a general explanation for variation in observed diversity-ecosystem variability relationships and highlights the importance of conserving regional species pools to help buffer ecosystems against predicted increases in environmental variability. © 2017 John Wiley & Sons Ltd/CNRS.

1996-2007 Interannual Spatio-Temporal Variability in Snowmelt in Two Montane Watersheds

NASA Astrophysics Data System (ADS)

Jepsen, S. M.; Molotch, N. P.; Rittger, K. E.

2009-12-01

Snowmelt is a primary water source for ecosystems within, and urban/agricultural centers near, mountain regions. Stream chemistry from montane catchments is controlled by the flowpaths of water from snowmelt and the timing and duration of snow coverage. A process level understanding of the variability in these processes requires an understanding of the effect of changing climate and anthropogenic loading on spatio-temporal snowmelt patterns. With this as our objective, we are applying a snow reconstruction model to two well-studied montane watersheds, Tokopah Basin (TOK), California and Green Lakes Valley (GLV), Colorado, to examine interannual variability in the timing and location of snowmelt in response to variable climate conditions during the period from 1996 to 2007. The reconstruction model back solves for snowmelt by combining surface energy fluxes, inferred from meteorological data, with sequences of melt season snow images derived from satellite data (i.e., snowmelt depletion curves). Preliminary model results for 2002 were tested against measured snow water equivalent (SWE) and hydrograph data for the two watersheds. The computed maximum SWE averaged over TOK and GLV were 94 cm (~+17% error) and 50.2 cm (~+1% error), respectively. We present an analysis of interannual variability in these errors, in addition to reconstructed snowmelt maps over different land cover types under changing climate conditions between 1996-2007, focusing on the variability with interannual variation in climate.

Temporal analysis of the frequency and duration of low and high streamflow: Years of record needed to characterize streamflow variability

USGS Publications Warehouse

Huh, S.; Dickey, D.A.; Meador, M.R.; Ruhl, K.E.

2005-01-01

A temporal analysis of the number and duration of exceedences of high- and low-flow thresholds was conducted to determine the number of years required to detect a level shift using data from Virginia, North Carolina, and South Carolina. Two methods were used - ordinary least squares assuming a known error variance and generalized least squares without a known error variance. Using ordinary least squares, the mean number of years required to detect a one standard deviation level shift in measures of low-flow variability was 57.2 (28.6 on either side of the break), compared to 40.0 years for measures of high-flow variability. These means become 57.6 and 41.6 when generalized least squares is used. No significant relations between years and elevation or drainage area were detected (P>0.05). Cluster analysis did not suggest geographic patterns in years related to physiography or major hydrologic regions. Referring to the number of observations required to detect a one standard deviation shift as 'characterizing' the variability, it appears that at least 20 years of record on either side of a shift may be necessary to adequately characterize high-flow variability. A longer streamflow record (about 30 years on either side) may be required to characterize low-flow variability. ?? 2005 Elsevier B.V. All rights reserved.

Variability of human corticospinal excitability tracks the state of action preparation.

PubMed

Klein-Flügge, Miriam C; Nobbs, David; Pitcher, Julia B; Bestmann, Sven

2013-03-27

Task-evoked trial-by-trial variability is a ubiquitous property of neural responses, yet its functional role remains largely unclear. Recent work in nonhuman primates shows that the temporal structure of neural variability in several brain regions is task-related. For example, trial-by-trial variability in premotor cortex tracks motor preparation with increasingly consistent firing rates and thus a decline in variability before movement onset. However, whether noninvasive measures of the variability of population activity available from humans can similarly track the preparation of actions remains unknown. We tested this by using single-pulse transcranial magnetic stimulation (TMS) over primary motor cortex (M1) to measure corticospinal excitability (CSE) at different times during action preparation. First, we established the basic properties of intrinsic CSE variability at rest. Then, during the task, responses (left or right button presses) were either directly instructed (forced choice) or resulted from a value decision (choice). Before movement onset, we observed a temporally specific task-related decline in CSE variability contralateral to the responding hand. This decline was stronger in fast-response compared with slow-response trials, consistent with data in nonhuman primates. For the nonresponding hand, CSE variability also decreased, but only in choice trials, and earlier compared with the responding hand, possibly reflecting choice-specific suppression of unselected actions. These findings suggest that human CSE variability measured by TMS over M1 tracks the state of motor preparation, and may reflect the optimization of preparatory population activity. This provides novel avenues in humans to assess the dynamics of action preparation but also more complex processes, such as choice-to-action transformations.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

Rainfall Patterns Analysis over Ampangan Muda, Kedah from 2007 - 2016

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

The scientific knowledge about climate change and climate variability over Malaysia pertaining to the extreme water-related disaster such as drought and flood. A deficit or increment in precipitation occurred over the past century becomes a useful tool to understand the climate change in Malaysia. The purpose of this work is to examine the rainfall patterns over Ampangan Muda, Kedah. Daily rainfall data is acquired from Malaysian Meteorological Department to analyse the temporal and trends of the monthly and annual rainfall over the study area from 2007 to 2016. The obtained results show that the temporal and patterns of the rainfall over Ampangan Muda, Kedah is largely affected by the regional phenomena such as monsoon, El Niño Southern Oscillation (ENSO), and the Madden-Julian Oscillation. In addition, backward trajectories analysis is also used to identify the patterns for long-range of synoptic circulation over the region.

An 8/15-channel Tx/Rx head neck RF coil combination with region-specific B1 + shimming for whole-brain MRI focused on the cerebellum at 7T.

PubMed

Pfaffenrot, Viktor; Brunheim, Sascha; Rietsch, Stefan H G; Koopmans, Peter J; Ernst, Thomas M; Kraff, Oliver; Orzada, Stephan; Quick, Harald H

2018-02-09

To design and evaluate an 8/15-channel transmit/receive (Tx/Rx) head-neck RF coil combination with region-specific B1+ shimming for whole-brain MRI with focus on improved functional MRI of the cerebellum at 7 T. An 8-channel transceiver RF head coil was combined with a 7-channel receive-only array. The noise parameters and acceleration capabilities of this 8Tx/15Rx coil setup were compared with a commercially available 1Tx/32Rx RF head coil. Region-specific 8-channel B1+ shimming was applied when using the 8Tx/15Rx RF coil. To evaluate the capability for functional MRI of the cerebellum, temporal SNR and statistical nonparametric maps for finger-tapping experiments with 14 healthy subjects were derived by applying a variable slice thickness gradient-echo echo-planar functional MRI sequence. The 8Tx/15Rx setup had a lower maximum noise correlation between channels, but higher average correlations compared with the 1Tx/32Rx coil. Both RF coils exhibited identical g-factors in the cerebellum with R = 3 acceleration. The enlarged FOV of the 8Tx/15Rx coil in combination with region-specific B1+ shimming increased homogeneity of the transmission field and temporal SNR in caudal cerebellar regions. Temporal SNR losses in cranial parts were reduced, resulting in more highly significant voxels in the caudally activated areas and identical patterns in the cranial cerebellar parts during a finger-tapping task. Compared with the 1Tx/32Rx RF coil, the presented 8Tx/15Rx RF coil combination successfully improves functional MRI of the human cerebellum at 7 T while maintaining whole-brain coverage. A clear temporal SNR gain in caudal cerebellar regions is shown. © 2018 International Society for Magnetic Resonance in Medicine.

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

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

NASA Technical Reports Server (NTRS)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

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.

The influence of prescribed fire and burn interval on fuel loads in four North Carolina forest ecosystems

Treesearch

M.J. Gavazzi; S.G. McNulty

2014-01-01

Prescribed fire is an important management tool in southern US forests, with more acres burned in the South than any other region of the US. Research from prescribed fire studies shows high temporal and spatial variability in available fuel loads due to physiographic, edaphic, meteorological and biological factors. In an effort to account for parts of this variation...

Remote Sensing and Problems of the Hydrosphere

NASA Technical Reports Server (NTRS)

Goldberg, E. D. (Editor)

1979-01-01

A discussion of freshwater and marine systems is presented including areas of the classification of lakes, identification and quantification of major functional groups of phytoplankton, sources and sinks of biochemical factors, and temporal and regional variability of surface features. Atmospheric processes linked to hydrospheric process through the transfer of matter via aerosols and gases are discussed. Particle fluxes to the aquatic environment and global geochemical problems are examined.

Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

NASA Astrophysics Data System (ADS)

Yang, Fan; Lu, Hui; Yang, Kun; He, Jie; Wang, Wei; Wright, Jonathon S.; Li, Chengwei; Han, Menglei; Li, Yishan

2017-11-01

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008-2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

Elucidating determinants of aerosol composition through particle-type-based receptor modeling

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Jeong, C.-H.; Slowik, J. G.; Chang, R. Y.-W.; Corbin, J. C.; Lu, G.; Mihele, C.; Rehbein, P. J. G.; Sills, D. M. L.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2011-03-01

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in Southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluating the internal and external mixing state of the characteristic particle-types. The nine factors identified helped to elucidate the coupled interactions of these determinants. Nitrate-laden dust was found to be the dominant type of locally emitted particles measured by ATOFMS. Several factors associated with aerosol transported to the site from intermediate local-to-regional distances were identified: the Organic factor was associated with a combustion source to the north-west; the ECOC Day factor was characterized by nearby local-to-regional carbonaceous emissions transported from the south-west during the daytime; and the Fireworks factor consisted of pyrotechnic particles from the Detroit region following holiday fireworks displays. Regional aerosol from farther emissions sources were reflected through three factors: two biomass burning factors and a highly chemically processed long range transport factor. The biomass burning factors were separated by PMF due to differences in chemical processing which were caused in part by the passage of two thunderstorm gust fronts with different air mass histories. The remaining two factors, ECOC Night and Nitrate Background, represented the night-time partitioning of nitrate to pre-existing particles of different origins. The distinct meteorological conditions observed during this month-long study in the summer of 2007 provided a unique range of temporal variability, enabling the elucidation of the determinants of aerosol chemical composition, including source emissions, chemical processing, and transport, at the Canada-US border. This paper presents the first study to characterize the coupled influences of these determinants on temporal variability in aerosol chemical composition using single particle-type-based receptor modelling.

Elucidating determinants of aerosol composition through particle-type-based receptor modeling

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Jeong, C.-H.; Slowik, J. G.; Chang, R. Y.-W.; Corbin, J. C.; Lu, G.; Mihele, C.; Rehbein, P. J. G.; Sills, D. M. L.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2011-08-01

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed at a semi-rural site in southern Ontario to characterize the size and chemical composition of individual particles. Particle-type-based receptor modelling of these data was used to investigate the determinants of aerosol chemical composition in this region. Individual particles were classified into particle-types and positive matrix factorization (PMF) was applied to their temporal trends to separate and cross-apportion particle-types to factors. The extent of chemical processing for each factor was assessed by evaluating the internal and external mixing state of the characteristic particle-types. The nine factors identified helped to elucidate the coupled interactions of these determinants. Nitrate-laden dust was found to be the dominant type of locally emitted particles measured by ATOFMS. Several factors associated with aerosol transported to the site from intermediate local-to-regional distances were identified: the Organic factor was associated with a combustion source to the north-west; the ECOC Day factor was characterized by nearby local-to-regional carbonaceous emissions transported from the south-west during the daytime; and the Fireworks factor consisted of pyrotechnic particles from the Detroit region following holiday fireworks displays. Regional aerosol from farther emissions sources was reflected through three factors: two Biomass Burning factors and a highly chemically processed Long Range Transport factor. The Biomass Burning factors were separated by PMF due to differences in chemical processing which were in part elucidated by the passage of two thunderstorm gust fronts with different air mass histories. The remaining two factors, ECOC Night and Nitrate Background, represented the night-time partitioning of nitrate to pre-existing particles of different origins. The distinct meteorological conditions observed during this month-long study in the summer of 2007 provided a unique range of temporal variability, enabling the elucidation of the determinants of aerosol chemical composition, including source emissions, chemical processing, and transport, at the Canada-US border. This paper presents the first study to elucidate the coupled influences of these determinants on temporal variability in aerosol chemical composition using single particle-type-based receptor modelling.

Spatio-temporal characteristics of PM10 concentration across Malaysia

NASA Astrophysics Data System (ADS)

Juneng, Liew; Latif, Mohd Talib; Tangang, Fredolin T.; Mansor, Haslina

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August-September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10-20 days quasi-biweekly (QBW) and 30-60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.

Teleconnection stationarity, variability and trends of the Southern Annular Mode (SAM) during the last millennium

NASA Astrophysics Data System (ADS)

Dätwyler, Christoph; Neukom, Raphael; Abram, Nerilie J.; Gallant, Ailie J. E.; Grosjean, Martin; Jacques-Coper, Martín; Karoly, David J.; Villalba, Ricardo

2017-11-01

The Southern Annular Mode (SAM) is the leading mode of atmospheric interannual variability in the Southern Hemisphere (SH) extra-tropics. Here, we assess the stationarity of SAM spatial correlations with instrumental and paleoclimate proxy data for the past millennium. The instrumental period shows that temporal non-stationarities in SAM teleconnections are not consistent across the SH land areas. This suggests that the influence of the SAM index is modulated by regional effects. However, within key-regions with good proxy data coverage (South America, Tasmania, New Zealand), teleconnections are mostly stationary over the instrumental period. Using different stationarity criteria for proxy record selection, we provide new austral summer and annual mean SAM index reconstructions over the last millennium. Our summer SAM reconstructions are very robust to changes in proxy record selection and the selection of the calibration period, particularly on the multi-decadal timescale. In contrast, the weaker performance and lower agreement in the annual mean SAM reconstructions point towards changing teleconnection patterns that may be particularly important outside the summer months. Our results clearly portend that the temporal stationarity of the proxy-climate relationships should be taken into account in the design of comprehensive regional and hemispherical climate reconstructions. The summer SAM reconstructions show no significant relationship to solar, greenhouse gas and volcanic forcing, with the exception of an extremely strong negative anomaly following the AD 1257 Samalas eruption. Furthermore, reconstructed pre-industrial summer SAM trends are very similar to trends obtained by model control simulations. We find that recent trends in the summer SAM lie outside the 5-95% range of pre-industrial natural variability.

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

Kumar, R.; Barth, M. C.; Nair, V. S.

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March-May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inlandmore » sites. In general, the model underestimates the observed BC mass concentrations. However, the model-observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average +/- standard deviation (representing spatial and temporal variability) BC mass concentration (1341 +/- 2353 ng m(-3)) in South Asia. BC emissions from residential (61 %) and industrial (23 %) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.« less

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

Kumar, R.; Barth, M. C.; Nair, V. S.

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March–May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inlandmore » sites. In general, the model underestimates the observed BC mass concentrations. However, the model–observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average ± standard deviation (representing spatial and temporal variability) BC mass concentration (1341 ± 2353 ng m -3) in South Asia. BC emissions from residential (61%) and industrial (23%) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.« less

Spatial δ18Osw-SSS relationship across the western tropical Pacific Ocean

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Conroy, J. L.; Wyman, A.; Read, D.

2017-12-01

Dynamic hydroclimate processes across the western tropical Pacific lead to strong spatial and temporal variability in δ18Osw and sea-surface salinity (SSS) across the western Pacific. Corals in this region have therefore provided key information about past SSS variability, as δ18Osw contributes strongly to coral δ18O across this region. However, uncertainties in the δ18Osw-SSS relationship across space and time often limit quantitative SSS reconstructions from such coral records. Recent work demonstrates considerable variability in the δ18Osw-SSS relationship across the Pacific, which may lead to over- or under-estimation of the contribution of SSS to coral δ18O, particularly across the western tropical Pacific (Conroy et al. 2017). Here we assess the spatial δ18Osw-SSS relationship across the dynamic western tropical Pacific, capitalizing on a transit between Subic Bay, Philippines and Townsville, Australia aboard the International Ocean Discovery program's JOIDES Resolution. Water samples and weather conditions were collected 3 times daily (6:00, 12:00, 18:00) en route, resulting in a network of 47 samples spaced at semi-regular 130-260 km intervals across the western Pacific from 14°N to 18°S. The route also crossed near long-term δ18Osw monitoring sites at Papua New Guinea and Palau (Conroy et al. 2017), allowing us to compare the spatial and temporal δ18Osw-SSS relationships at these sites and test the space-for-time assumption. We present the δ18Osw-SSS relationship across this region, compare the relationship across space and time, and discuss the implications of our results for SSS reconstructions from coral δ18O.

On Relations Between the Ozonosphere and the General Atmospheric Circulation in Tropics

NASA Astrophysics Data System (ADS)

Kuznetsov, G. I.; Kramarova, N. A.

2006-05-01

The main features of temporal and spatial ozone distribution over tropics and their relations with peculiarities of the general atmospheric circulation are obtained using the total ozone data for the tropical region (Ozone Data for the World and TOMS (version 8)). Among the factors influencing ozone regime in tropics the properties of the region, like intertropical convergence zone and a structure of tropical tropopause, and processes such as stratosphere-troposphere exchange, migration of ozone equator, Quasi Biennial Oscillation are analyzed. To investigate the long term variability of tropical ozone detrended and de-seasonalized fields of TOMS observations are analyzed by means of EOF method. The first four EOFs explain about 75% of residual total ozone variability in tropical region. Spatial patterns of EOFs and corresponding time coefficients are closely connected with the Quasi-Biennial Oscillation (EOF-1), the 11-years Solar Cycle (EOF-2), the QBO-annual beat (EOF-3) and with the South Oscillation (EOF-4) correspondingly. The detailed analyses of temporal and spatial distribution of ozone EOF patterns reveals a distinct change of ozone fields to the both sides of equator at 10-15 latitude as well as at the zones of tropical tropopause break. A time delay of ozone QBO phase is observed while moving towards higher latitudes. Some features of the tropical ozone regime manifest themselves in the peculiarities of Antarctic Ozone Anomalies. A time variability of ozone QBO passes three months ahead of the Singapore 30 mbar zonal wind. Obtained relations let us to construct a linear regression model based on EOF decomposition to estimate total ozone monthly means over tropics. This model is successfully applied to predict 30 mbar zonal wind in dependence on tropical ozone behavior.

Carbon monoxide (CO) emissions and its tropospheric variability over Pakistan using satellite-sensed data

NASA Astrophysics Data System (ADS)

ul-Haq, Zia; Rana, Asim Daud; Ali, Muhammad; Mahmood, Khalid; Tariq, Salman; Qayyum, Zarmina

2015-08-01

This study presents major anthropogenic sources of carbon monoxide (CO) in Pakistan and discusses the spatio-temporal variability of tropospheric CO over Pakistan and neighboring regions of Afghanistan, India and Iran for a period from 2003 to 2012 using satellite-sensed (AIRS/AMSU) data. The results show a large spatio-temporal variability of CO over the study region mostly associated with anthropogenic activities such as crop residue burning, vehicular transport, and electricity and energy generation, and local meteorology. The annual mean value of tropospheric CO is observed to be 115 ± 2 ppbv that remains almost steady during the study period with decadal increase of only 2%. Due to more anthropogenic emissions of CO and its transport, the eastern zone shows a higher average value of 122 ± 2 ppbv with 2.7% decadal increase than the western zone (111 ± 3 ppbv with 1.4% decadal increase). Elevated concentrations of CO have been observed over the Indo-Gangetic Basin, Lahore, Karachi, and Delhi. During the study period large fluctuations in CO mean monthly values are found ranging from 99 ppbv to 131 ppbv. The fact that, in spite of a large increase in the CO emissions from 2003 to 2012, its average concentration remains almost stable indicates that a large scale regional transport contributes substantially to the tropospheric CO. Carbon monoxide concentrations exhibit a strong seasonal pattern with maximum amplitude in spring and minimum in autumn. July is found to have the highest decadal increasing trend of 13% followed by August at 8%, whereas May has the highest decreasing trend of -8% followed by November at -4.4%.

Winter wheat mapping combining variations before and after estimated heading dates

NASA Astrophysics Data System (ADS)

Qiu, Bingwen; Luo, Yuhan; Tang, Zhenghong; Chen, Chongcheng; Lu, Difei; Huang, Hongyu; Chen, Yunzhi; Chen, Nan; Xu, Weiming

2017-01-01

Accurate and updated information on winter wheat distribution is vital for food security. The intra-class variability of the temporal profiles of vegetation indices presents substantial challenges to current time series-based approaches. This study developed a new method to identify winter wheat over large regions through a transformation and metric-based approach. First, the trend surfaces were established to identify key phenological parameters of winter wheat based on altitude and latitude with references to crop calendar data from the agro-meteorological stations. Second, two phenology-based indicators were developed based on the EVI2 differences between estimated heading and seedling/harvesting dates and the change amplitudes. These two phenology-based indicators revealed variations during the estimated early and late growth stages. Finally, winter wheat data were extracted based on these two metrics. The winter wheat mapping method was applied to China based on the 250 m 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) time series datasets. Accuracy was validated with field survey data, agricultural census data, and Landsat-interpreted results in test regions. When evaluated with 653 field survey sites and Landsat image interpreted data, the overall accuracy of MODIS-derived images in 2012-2013 was 92.19% and 88.86%, respectively. The MODIS-derived winter wheat areas accounted for over 82% of the variability at the municipal level when compared with agricultural census data. The winter wheat mapping method developed in this study demonstrates great adaptability to intra-class variability of the vegetation temporal profiles and has great potential for further applications to broader regions and other types of agricultural crop mapping.

Spatial and temporal variability in aerosol properties over the Mediterranean basin based on 6-year (2000-2006) MODIS data

NASA Astrophysics Data System (ADS)

Papadimas, C. D.; Hatzianastassiou, N.; Mihalopoulos, N.; Querol, X.; Vardavas, I.

2008-06-01

The temporal variability of aerosol optical properties is investigated over the broader Mediterranean basin, with emphasis on aerosol optical depth (AOD) that is an effective measure of aerosol load. The study is performed using Collection 005 Level-3 mean daily spectral aerosol data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the Terra and Aqua satellites, which cover the 6-year period from 2000 to 2006. The results of our analysis reveal a significant interannual variability of AOD in the study region. Specifically, the regional mean visible AOD over land and ocean has decreased over the period 2000-2006 by 20% in relative percentage terms (or by 0.04 in absolute terms). This tendency is statistically significant according to the Man-Kendall test. However, the decreasing tendency of AOD is not uniform over the whole basin. It appears mainly in the western parts of Iberian, Italian, and Balkan peninsulas (and coastal areas), as well as in the southern Anatolian peninsula. The analysis for summer (June to September) and winter (November to March) seasons revealed different tendencies in both AOD and precipitation. The summer-period AOD has decreased by 0.04 (or by 14%) probably due to decreased emission rates of anthropogenic pollution. In contrast, the winter AOD has increased by 0.03 (or 19%) mainly related to decreased precipitation (associated with an increasing tendency in the NAO index). The decreasing tendency in MODIS AOD is in good agreement with corresponding AOD tendencies based on data from Aerobot Robotic Network (AERONET) stations in the study region and ground based PM10 measurements at selected stations.

Variability in vegetation effects on density and nesting success of grassland birds

USGS Publications Warehouse

Winter, Maiken; Johnson, Douglas H.; Shaffer, Jill A.

2005-01-01

The structure of vegetation in grassland systems, unlike that in forest systems, varies dramatically among years on the same sites, and among regions with similar vegetation. The role of this variation in vegetation structure on bird density and nesting success of grassland birds is poorly understood, primarily because few studies have included sufficiently large temporal and spatial scales to capture the variation in vegetation structure, bird density, or nesting success. To date, no large-scale study on grassland birds has been conducted to investigate whether grassland bird density and nesting success respond similarly to changes in vegetation structure. However, reliable management recommendations require investigations into the distribution and nesting success of grassland birds over larger temporal and spatial scales. In addition, studies need to examine whether bird density and nesting success respond similarly to changing environmental conditions. We investigated the effect of vegetation structure on the density and nesting success of 3 grassland-nesting birds: clay-colored sparrow (Spizella pallida), Savannah sparrow (Passerculus sandwichensis), and bobolink (Dolichonyx oryzivorus) in 3 regions of the northern tallgrass prairie in 1998-2001. Few vegetation features influenced the densities of our study species, and each species responded differently to those vegetation variables. We could identify only 1 variable that clearly influenced nesting success of 1 species: clay-colored sparrow nesting success increased with increasing percentage of nest cover from the surrounding vegetation. Because responses of avian density and nesting success to vegetation measures varied among regions, years, and species, land managers at all times need to provide grasslands with different types of vegetation structure. Management guidelines developed from small-scale, short-term studies may lead to misrepresentations of the needs of grassland-nesting birds.

Variability of Upper-Tropospheric Precipitable from Satellite and Model Reanalysis Datasets

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Iwai, Hisaki

1999-01-01

Numerous datasets have been used to quantify water vapor and its variability in the upper-troposphere from satellite and model reanalysis data. These investigations have shown some usefulness in monitoring seasonal and inter-annual variations in moisture either globally, with polar orbiting satellite data or global model output analysis, or regionally, with the higher spatial and temporal resolution geostationary measurements. The datasets are not without limitations, however, due to coverage or limited temporal sampling, and may also contain bias in their representation of moisture processes. The research presented in this conference paper inter-compares the NVAP, NCEP/NCAR and DAO reanalysis models, and GOES satellite measurements of upper-tropospheric,precipitable water for the period from 1988-1994. This period captures several dramatic swings in climate events associated with ENSO events. The data are evaluated for temporal and spatial continuity, inter-compared to assess reliability and potential bias, and analyzed in light of expected trends due to changes in precipitation and synoptic-scale weather features. This work is the follow-on to previous research which evaluated total precipitable water over the same period. The relationship between total and upper-level precipitable water in the datasets will be discussed as well.

Temporal Variability and Stability in Infant-Directed Sung Speech: Evidence for Language-Specific Patterns

ERIC Educational Resources Information Center

Falk, Simone

2011-01-01

In this paper, sung speech is used as a methodological tool to explore temporal variability in the timing of word-internal consonants and vowels. It is hypothesized that temporal variability/stability becomes clearer under the varying rhythmical conditions induced by song. This is explored cross-linguistically in German--a language that exhibits a…

Regional sea level projections with observed gauge, altimeter and reconstructed data along China coast

NASA Astrophysics Data System (ADS)

Du, L.; Shi, H.; Zhang, S.

2017-12-01

Acting as the typical shelf seas in northwest Pacific Ocean, regional sea level along China coasts exhibits complicated and multiscale spatial-temporal characteristics under circumstance of global change. In this paper, sea level variability is investigated with tide gauges records, satellite altimetry data, reconstructed sea surface height, and CMIP simulation fields. Sea level exhibits the interannual variability imposing on a remarkable sea level rising in the China seas and coastal region, although its seasonal signals are significant as the results of global ocean. Sea level exhibits faster rising rate during the satellite altimetry era, nearly twice to the rate during the last sixty years. AVISO data and reconstructed sea surface heights illustrate good correlation coefficient, more than 0.8. Interannual sea level variation is mainly modulated by the low-frequency variability of wind fields over northern Pacific Ocean by local and remote processes. Meanwhile sea level varies obviously by the transport fluctuation and bimodality path of Kuroshio. Its variability possibly linked to internal variability of the ocean-atmosphere system influenced by ENSO oscillation. China Sea level have been rising during the 20th century, and are projected to continue to rise during this century. Sea level can reach the highest extreme level in latter half of 21st century. Modeled sea level including regional sea level projection combined with the IPCC climate scenarios play a significant role on coastal storm surge evolution. The vulnerable regions along the ECS coast will suffer from the increasing storm damage with sea level variations.

Emotions induced by intracerebral electrical stimulation of the temporal lobe.

PubMed

Meletti, Stefano; Tassi, Laura; Mai, Roberto; Fini, Nicola; Tassinari, Carlo Alberto; Russo, Giorgio Lo

2006-01-01

To assess the quality and frequency of emotions induced by intracerebral electrical stimulation of the temporal lobe. Behavioral responses were obtained by electrical stimulation in 74 patients undergoing presurgical video-stereo-EEG monitoring for drug-resistant epilepsy. Intracerebral electrical stimulation was performed by delivering trains of electrical stimuli of alternating polarity; the intensity could vary from 0.2 to 3 mA. Stimulation frequency was 1 Hz or 50 Hz. Nine hundred thirty-eight stimulation procedures were performed. Seventy-nine emotional responses (ERs) were obtained (8.4%). Of these, 67 were "fear responses." Sad feelings were evoked 3 times, happy-pleasant feelings 9 times. Anger and disgust were never observed. The following variables affected the incidence of ER: (a) Anatomical site of stimulation. ERs (always fear) were maximal at the amygdala (12%) and minimal for lateral neocortical stimulation (3%, p < 0.01). (b) Pathology. Stimulation of a temporal lobe with hippocampal sclerosis was associated with a lower frequency of ERs compared with stimulation of a temporal lobe with no evidence of atrophy in the medial temporal structures. (c) Stimulation frequency. ERs were 12% at 50 Hz versus 6.0% at 1 Hz (p < 0.01). (d) Gender. In women fear responses were 16% compared with 3% in men (p < 0.01). There were no gender differences when analyzing nonemotional responses. These data confirm the role of the medial temporal lobe region in the expression of emotions, especially fear-related behaviors. Fear was observed more frequently in the absence of medial temporal sclerosis, supporting the hypothesis that emotional behaviors induced by stimulation are positive phenomena, strictly related to the physiological function of these regions. Further investigations should address why women express fear behaviors more frequently than men.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Geospatial-temporal distribution of Tegumentary Leishmaniasis in Colombia (2007–2016)

PubMed Central

Herrera, Giovanny; Pradilla, Iván; Vera, Mauricio

2018-01-01

Background Tegumentary Leishmaniasis (TL) is a neglected disease with worldwide distribution and considered a public health problem, especially in Latin America. In Colombia, the governmental epidemiological surveillance system (SIVIGILA) is responsible for collecting information on the presentation of cases of TL from each of the municipalities and departments. In absence of a study compiling and analyzing currently available metadata of TL in Colombia, this study describes the geospatial-temporal distribution of TL and identifies the regions of the country on which prevention measures should be established in order to control the disease. Methodology/Principal findings This is an exploratory descriptive analysis of the distribution of TL in Colombia. Information was collected on new cases of the disease during the years 2007–2016 from the Colombian reporting system (SIVIGILA). Incidence calculations were made based on population estimates by departments and biogeographical regions. Time evolution is shown in biennial maps. A 10-year series was analyzed, showing that the Amazon region is the most affected in terms of incidence, while the Andean region has the highest number of cases with a high variability among the departments that make it up. In those departments where there is a greater reported diversity of vector species, a large number of cases was observed. Conclusions/Significance Transmission dynamics of TL in Colombia in the past 10 years have been variable, with a greater concentration of cases in the central and southern departments. The present study contributes to improve the understanding of the patterns of distribution of TL in Colombia and can be a basis for future studies of impact evaluation of Health policies in the country and the region. PMID:29624582

Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

NASA Astrophysics Data System (ADS)

Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

2010-08-01

An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima

2017-01-01

We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

Convective organization in the Pacific ITCZ: Merging OLR, TOVS, and SSM/I information

NASA Technical Reports Server (NTRS)

Hayes, Patrick M.; Mcguirk, James P.

1993-01-01

One of the most striking features of the planet's long-time average cloudiness is the zonal band of concentrated convection lying near the equator. Large-scale variability of the Intertropical Convergence Zone (ITCZ) has been well documented in studies of the planetary spatial scales and seasonal/annual/interannual temporal cycles of convection. Smaller-scale variability is difficult to study over the tropical oceans for several reasons. Conventional surface and upper-air data are virtually non-existent in some regions; diurnal and annual signals overwhelm fluctuations on other time scales; and analyses of variables such as geopotential and moisture are generally less reliable in the tropics. These problems make the use of satellite data an attractive alternative and the preferred means to study variability of tropical weather systems.

Cross-country transferability of multi-variable damage models

NASA Astrophysics Data System (ADS)

Wagenaar, Dennis; Lüdtke, Stefan; Kreibich, Heidi; Bouwer, Laurens

2017-04-01

Flood damage assessment is often done with simple damage curves based only on flood water depth. Additionally, damage models are often transferred in space and time, e.g. from region to region or from one flood event to another. Validation has shown that depth-damage curve estimates are associated with high uncertainties, particularly when applied in regions outside the area where the data for curve development was collected. Recently, progress has been made with multi-variable damage models created with data-mining techniques, i.e. Bayesian Networks and random forest. However, it is still unknown to what extent and under which conditions model transfers are possible and reliable. Model validations in different countries will provide valuable insights into the transferability of multi-variable damage models. In this study we compare multi-variable models developed on basis of flood damage datasets from Germany as well as from The Netherlands. Data from several German floods was collected using computer aided telephone interviews. Data from the 1993 Meuse flood in the Netherlands is available, based on compensations paid by the government. The Bayesian network and random forest based models are applied and validated in both countries on basis of the individual datasets. A major challenge was the harmonization of the variables between both datasets due to factors like differences in variable definitions, and regional and temporal differences in flood hazard and exposure characteristics. Results of model validations and comparisons in both countries are discussed, particularly in respect to encountered challenges and possible solutions for an improvement of model transferability.

Flood loss model transfer: on the value of additional data

NASA Astrophysics Data System (ADS)

Schröter, Kai; Lüdtke, Stefan; Vogel, Kristin; Kreibich, Heidi; Thieken, Annegret; Merz, Bruno

2017-04-01

The transfer of models across geographical regions and flood events is a key challenge in flood loss estimation. Variations in local characteristics and continuous system changes require regional adjustments and continuous updating with current evidence. However, acquiring data on damage influencing factors is expensive and therefore assessing the value of additional data in terms of model reliability and performance improvement is of high relevance. The present study utilizes empirical flood loss data on direct damage to residential buildings available from computer aided telephone interviews that were carried out after the floods in 2002, 2005, 2006, 2010, 2011 and 2013 mainly in the Elbe and Danube catchments in Germany. Flood loss model performance is assessed for incrementally increased numbers of loss data which are differentiated according to region and flood event. Two flood loss modeling approaches are considered: (i) a multi-variable flood loss model approach using Random Forests and (ii) a uni-variable stage damage function. Both model approaches are embedded in a bootstrapping process which allows evaluating the uncertainty of model predictions. Predictive performance of both models is evaluated with regard to mean bias, mean absolute and mean squared errors, as well as hit rate and sharpness. Mean bias and mean absolute error give information about the accuracy of model predictions; mean squared error and sharpness about precision and hit rate is an indicator for model reliability. The results of incremental, regional and temporal updating demonstrate the usefulness of additional data to improve model predictive performance and increase model reliability, particularly in a spatial-temporal transfer setting.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography.

PubMed

Ozker, Muge; Schepers, Inga M; Magnotti, John F; Yoshor, Daniel; Beauchamp, Michael S

2017-06-01

Human speech can be comprehended using only auditory information from the talker's voice. However, comprehension is improved if the talker's face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl's gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech.

Comparing three models to estimate transpiration of desert shrubs

NASA Astrophysics Data System (ADS)

Xu, Shiqin; Yu, Zhongbo; Ji, Xibin; Sudicky, Edward A.

2017-07-01

The role of environmental variables in controlling transpiration (Ec) is an important, but not well-understood, aspect of transpiration modeling in arid desert regions. Taking three dominant desert shrubs, Haloxylon ammodendron, Nitraria tangutorum, and Calligonum mongolicum, as examples, we aim to evaluate the applicability of three transpiration models, i.e. the modified Jarvis-Stewart model (MJS), the simplified process-based model (BTA), and the artificial neural network model (ANN) at different temporal scales. The stem sap flow of each species was monitored using the stem heat balance approach over both the 2014 and 2015 main growing seasons. Concurrent environmental variables were also measured with an automatic weather station. The ANN model generally produced better simulations of Ec than the MJS and BTA models at both hourly and daily scales, indicating its advantage in solving complicated, nonlinear problems between transpiration rate and environmental driving forces. The solar radiation and vapor pressure deficit were crucial variables in modeling Ec for all three species. The performance of the MJS and ANN models was significantly improved by incorporating root-zone soil moisture. We also found that the difference between hourly and daily fitted parameter values was considerable for the MJS and BTA models. Therefore, these models need to be recalibrated when applied at different temporal scales. This study provides insights regarding the application and performance of current transpiration models in arid desert regions, and thus provides a deeper understanding of eco-hydrological processes and sustainable ecosystem management at the study site.

Climatic variability of soil water in the American Midwest: Part 2. Spatio-temporal analysis

NASA Astrophysics Data System (ADS)

Georgakakos, Konstantine P.; Bae, Deg-Hyo

1994-11-01

A study of the model-estimated soil water, aggregated over three large drainage basins of the Midwestern USA, is reported. The basin areas are in the range from 2000 km 2 to 3500 km 2, and allow the study of mesoscale (1000-10000 km 2) soil water features. In each case, a conceptual hydrologic model was used to produce upper and lower soil water estimates that are consistent with the atmospheric forcing of daily precipitation, potential evapotranspiration and air temperature, and with the observed daily streamflow divergence over a 40 year period. It is shown that the water contents of the upper and lower soil reach peaks in different months, with the soil column being most saturated in June, when the area is prone to serious flooding. Temporal and spatial features of the variability of model-estimated soil water content are identified. The autocorrelation function of monthly averaged soil water shows that the upper soil water remains persistent for about a season, whereas the persistence of the lower soil water extends to several seasons. The soil water estimates of the three study basins exhibit strong similarities in annual cycles and interannual variability. It is shown that the frequency of significant positive (wet) soil water anomalies that extend over a 2° × 2° region is lower than that of significant negative (dry) ones of the same extent in this region of the USA.

Temporal change in biological community structure in the Fountain Creek basin, Colorado, 2001-2008

USGS Publications Warehouse

Zuellig, Robert E.; Bruce, James F.; Stogner, Sr., Robert W.

2010-01-01

In 2001, the U.S. Geological Survey, in cooperation with Colorado Springs City Engineering, began a study to better understand the relations between environmental characteristics and biological communities in the Fountain Creek basin in order to aide water-resource management and guide future monitoring activities. To accomplish this task, environmental (streamflow, habitat, and water chemistry) and biological (fish and macroinvertebrate) data were collected annually at 24 sites over a 6- or 8-year period (fish, 2003 to 2008; macroinvertebrates, 2001 to 2008). For this report, these data were first analyzed to determine the presence of temporal change in macroinvertebrate and fish community structure among years using nonparametric multivariate statistics. Where temporal change in the biological communities was found, these data were further analyzed using additional nonparametric multivariate techniques to determine which subset of selected streamflow, habitat, or water-chemistry variables best described site-specific changes in community structure relative to a gradient of urbanization. This study identified significant directional patterns of temporal change in macroinvertebrate and fish community structure at 15 of 24 sites in the Fountain Creek basin. At four of these sites, changes in environmental variables were significantly correlated with the concurrent temporal change identified in macroinvertebrate and fish community structure (Monument Creek above Woodmen Road at Colorado Springs, Colo.; Monument Creek at Bijou Street at Colorado Springs, Colo.; Bear Creek near Colorado Springs, Colo.; Fountain Creek at Security, Colo.). Combinations of environmental variables describing directional temporal change in the biota appeared to be site specific as no single variable dominated the results; however, substrate composition variables (percent substrate composition composed of sand, gravel, or cobble) collectively were present in 80 percent of the environmental variable subsets that were significantly correlated with temporal change in the macroinvertebrate and fish community structure. Other important environmental variables related to temporal change in the biological community structure included those describing channel form (streambank height) and streamflow (normalized annual mean daily flow, high flood-pulse count). Site-specific results from this study were derived from a relatively small number of observations (6 or 8 years of data); therefore, additional years of data may reveal other sites with temporal change in biological community structure, or could define stronger and more consistent linkages between environmental variables and observed temporal change. Likewise current variable subsets could become weaker. Nonetheless, there were several sites where temporal change was detected in this study that could not be explained by the available environmental variables studied herein. Modification of current data-collection activities may be necessary to better understand site-specific temporal relations between biological communities and environmental variables.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern US

USGS Publications Warehouse

Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.

2015-01-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

PubMed

Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

2015-11-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean

PubMed Central

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2018-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000–12/2012) and Aqua (7/2002–12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations. PMID:29755508

Spatiotemporal variability and contribution of different aerosol types to the aerosol optical depth over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-11-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ˜ 0.22 ± 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for ˜ 51, ˜ 34 and ˜ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ˜ 40, ˜ 34 and ˜ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

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.

Spatiotemporal Variability and Contribution of Different Aerosol Types to the Aerosol Optical Depth over the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Poeschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1deg × 0.1deg gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is approx. 0.22 +/- 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for approx. 51, approx. 34 and approx. 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account approx. 40, approx. 34 and approx. 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean.

PubMed

Georgoulias, Aristeidis K; Alexandri, Georgia; Kourtidis, Konstantinos A; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000-12/2012) and Aqua (7/2002-12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD 550 ) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD 550 . The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD 550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD 550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD 550 over the sea, based on MODIS Terra and Aqua observations.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Effects of temporal averaging on short-term irradiance variability under mixed sky conditions

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.

2018-05-01

Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers of photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range of different temporal resolutions and a systematic analysis of the effects of temporal averaging on the representation of variability is lacking. Using high-resolution surface irradiance data with original temporal resolutions between 0.01 and 1 s from six different locations in the Northern Hemisphere, we characterize the changes in representation of temporal variability resulting from time averaging. In this analysis, we condition all data to states of mixed skies, which are the most potentially problematic in terms of local PV power volatility. Statistics of clear-sky index k* and its increments Δk*τ (i.e., normalized surface irradiance and changes therein over specified intervals of time) are considered separately. Our results indicate that a temporal averaging time scale of around 1 s marks a transition in representing single-point irradiance variability, such that longer averages result in substantial underestimates of variability. Higher-resolution data increase the complexity of data management and quality control without appreciably improving the representation of variability. The results do not show any substantial discrepancies between locations or seasons.

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.; Haggerty, Roy

2013-01-01

1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year. 2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony. 3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences. 4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing. 5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.

On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

2016-12-01

Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product. These results highlight that the role of other surface variables presenting a strong seasonal variability (like vegetation cover, possibly irrigation) is not accounted for similarly in both the model and the product, and that further work is needed to explore these discrepancies.

Sources of black carbon aerosols in South Asia and surrounding regions during the Integrated Campaign for Aerosols, Gases and Radiation Budget (ICARB)

DOE PAGES

Kumar, R.; Barth, M. C.; Nair, V. S.; ...

2015-05-19

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March–May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inlandmore » sites. In general, the model underestimates the observed BC mass concentrations. However, the model–observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average ± standard deviation (representing spatial and temporal variability) BC mass concentration (1341 ± 2353 ng m -3) in South Asia. BC emissions from residential (61%) and industrial (23%) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.« less

A MAD model for gamma-ray burst variability

NASA Astrophysics Data System (ADS)

Lloyd-Ronning, Nicole M.; Dolence, Joshua C.; Fryer, Christopher L.

2016-09-01

We present a model for the temporal variability of long gamma-ray bursts (GRBs) during the prompt phase (the highly variable first 100 s or so), in the context of a magnetically arrested disc (MAD) around a black hole. In this state, sufficient magnetic flux is held on to the black hole such that it stalls the accretion near the inner region of the disc. The system transitions in and out of the MAD state, which we relate to the variable luminosity of the GRB during the prompt phase, with a characteristic time-scale defined by the free-fall time in the region over which the accretion is arrested. We present simple analytic estimates of the relevant energetics and time-scales, and compare them to GRB observations. In particular, we show how this model can reproduce the characteristic one second time-scale that emerges from various analyses of the prompt emission light curve. We also discuss how our model can accommodate the potentially physically important correlation between a burst quiescent time and the duration of its subsequent pulse.

Effect of climate-driven changes in species composition on regional emission capacities of biogenic compounds

NASA Astrophysics Data System (ADS)

Schurgers, G.; Arneth, A.; Hickler, T.

2011-11-01

Regional or global modeling studies of dynamic vegetation often represent vegetation by large functional units (plant functional types (PFTs)). For simulation of biogenic volatile organic compounds (BVOC) in these models, emission capacities, which give the emission under standardized conditions, are provided as an average value for a PFT. These emission capacities thus hide the known heterogeneity in emission characteristics that are not straightforwardly related to functional characteristics of plants. Here we study the effects of the aggregation of species-level information on emission characteristics at PFT level. The roles of temporal and spatial variability are assessed for Europe by comparing simulations that represent vegetation by dominant tree species on the one hand and by plant functional types on the other. We compare a number of time slices between the Last Glacial Maximum (21,000 years ago) and the present day to quantify the effects of dynamically changing vegetation on BVOC emissions. Spatial heterogeneity of emission factors is studied with present-day simulations. We show that isoprene and monoterpene emissions are of similar magnitude in Europe when the simulation represents dominant European tree species, which indicates that simulations applying typical global-scale emission capacities for PFTs tend to overestimate isoprene and underestimate monoterpene emissions. Moreover, both spatial and temporal variability affect emission capacities considerably, and by aggregating these to PFT level averages, one loses the information on local heterogeneity. Given the reactive nature of these compounds, accounting for spatial and temporal heterogeneity can be important for studies of their fate in the atmosphere.

Composition and daytime vertical distribution of the ichthyoplankton assemblage in the Central Cantabrian Sea shelf, during summer: An Eulerian study

NASA Astrophysics Data System (ADS)

Rodriguez, J. M.; Gonzalez-Pola, C.; Lopez-Urrutia, A.; Nogueira, E.

2011-09-01

During summer, wind driven coastal upwelling dominates in the Central Cantabrian Sea (southern Bay of Biscay). Nevertheless, atmospheric forcing is highly variable and wind pulses may cause noticeable and fast hydrographic responses in the shelf region. In this paper, the composition and vertical distribution of the summer ichthyoplankton assemblage during the daytime at a fixed station, located on the Central Cantabrian Sea shelf, are documented. Also, the impact of a short-time scale hydrographic event on the abundance and structure of the larval fish assemblage is examined. Significant small-scale temporal hydrographic variability was observed. Currents showed changes in speed and direction and significant changes in thermocline depth were also observed. A total of 34 taxa of fish larvae were identified. Engraulis encrasicolus eggs and larvae of the shelf-dwelling species Trachurus trachurus, Capros aper and E. encrasicolus dominated the ichthyoplankton assemblage. The distribution of E. encrasicolus eggs and fish larvae was vertically structured. E. encrasicolus egg concentration increased exponentially towards the surface. Fish larvae showed a subsurface peak of concentration and their vertical distribution was not conditioned by thermocline depths. The short term hydrographic event did not affect the vertical distribution of fish larvae but it accounted for significant temporal changes in larval fish assemblage structure and abundance. Results suggest that temperature and light intensity are important factors in the vertical distribution of fish larvae. They also indicate that the temporal monitoring of the larval fish assemblage in this region requires multiple sampling sites.

Home ranges of lions in the Kalahari, Botswana exhibit vast sizes and high temporal variability.

PubMed

Zehnder, André; Henley, Stephen; Weibel, Robert

2018-06-01

The central Kalahari region in Botswana is one of the few remaining ecosystems with a stable lion population. Yet, relatively little is known about the ecology of the lions there. As an entry point, home range estimations provide information about the space utilization of the studied animals. The home ranges of eight lions in this region were determined to investigate their spatial overlaps and spatiotemporal variations. We found that, except for MCP, all home range estimators yielded comparable results regarding size and shape. The home ranges of all individuals were located predominantly inside the protected reserves. Their areas were among the largest known for lions with 1131 - 4314km 2 (95%), with no significant differences between males and females. Numerous overlaps between lions of different sexes were detected, although these originate from different groups. A distance chart confirmed that most of these lions directly encountered each other once or several times. Strong temporal variations of the home ranges were observed that did not match a seasonal pattern. The exceptionally large home ranges are likely to be caused by the sparse and dynamic prey populations. Since the ungulates in the study area move in an opportunistic way, too, strong spatiotemporal home range variations emerge. This can lead to misleading home ranges. We therefore recommend clarifying the stability of the home ranges by applying several levels of temporal aggregation. The lack of strict territoriality is likely an adaptation to the variable prey base and the high energetic costs associated with defending a large area. Copyright © 2018 Elsevier GmbH. All rights reserved.

Cognitive and functional correlates of accelerated long-term forgetting in temporal lobe epilepsy.

PubMed

Audrain, Samantha; McAndrews, Mary P

2018-03-30

While we know that hippocampal dysfunction is responsible for the memory deficits that patients with temporal lobe epilepsy exhibit at relatively short study-test delays, the role of this region in accelerated long-term forgetting (ALF) is not yet clear. In the present study, we probed the role of the hippocampus in ALF by directly comparing memory for associations to memory that could be supported by item recognition during a forced choice recognition task over delays ranging from 15-min to 72-h. We additionally examined resting-state functional connectivity between the hippocampus and cortical regions known to be involved in processing these types of stimuli, as well as the relationship between ALF and various clinical variables including structural abnormality in the hippocampus, lateralization of epileptic focus, presence of seizures across the retention period, and standardized composite memory scores. We found evidence of accelerated forgetting for item stimuli (but not associative stimuli) by 6 h post-learning, which became statistically reliable by 72-h. This finding suggests that unlike controls, patients were unable to utilize novelty to reject the incorrect object-scene pair. While none of the examined clinical variables were related to long-term forgetting, reduced resting-state functional connectivity between the affected anterior hippocampus and unaffected lateral temporal cortex predicted forgetting of item stimuli over the 72-h delay. Implications for the role of the hippocampus in accelerated long-term forgetting, and existing theories of systems consolidation in this context are discussed. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Regional and temporal variability of melts during a Cordilleran magma pulse: Age and chemical evolution of the jurassic arc, eastern mojave desert, California

USGS Publications Warehouse

Barth, A.P.; Wooden, J.L.; Miller, David; Howard, Keith A.; Fox, Lydia; Schermer, Elizabeth R.; Jacobson, C.E.

2017-01-01

Intrusive rock sequences in the central and eastern Mojave Desert segment of the Jurassic Cordilleran arc of the western United States record regional and temporal variations in magmas generated during the second prominent pulse of Mesozoic continental arc magmatism. U/Pb zircon ages provide temporal control for describing variations in rock and zircon geochemistry that reflect differences in magma source components. These source signatures are discernible through mixing and fractionation processes associated with magma ascent and emplacement. The oldest well-dated Jurassic rocks defining initiation of the Jurassic pulse are a 183 Ma monzodiorite and a 181 Ma ignimbrite. Early to Middle Jurassic intrusive rocks comprising the main stage of magmatism include two high-K calc-alkalic groups: to the north, the deformed 183–172 Ma Fort Irwin sequence and contemporaneous rocks in the Granite and Clipper Mountains, and to the south, the 167–164 Ma Bullion sequence. A Late Jurassic suite of shoshonitic, alkali-calcic intrusive rocks, the Bristol Mountains sequence, ranges in age from 164 to 161 Ma and was emplaced as the pulse began to wane. Whole-rock and zircon trace-element geochemistry defines a compositionally coherent Jurassic arc with regional and secular variations in melt compositions. The arc evolved through the magma pulse by progressively greater input of old cratonic crust and lithospheric mantle into the arc magma system, synchronous with progressive regional crustal thickening.

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.

2015-01-01

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

Lateglacial climate reconstruction on the Bolivian Altiplano inferred from paleoglaciers and paleolakes

NASA Astrophysics Data System (ADS)

Martin, Léo; Blard, Pierre-Henri; Lavé, Jérôme; Prémaillon, Mélody; Jomelli, Vincent; Brunstein, Daniel; Lupker, Maarten; Charreau, Julien; Mariotti, Véronique; Condom, Thomas; Bourles, Didier

2016-04-01

Recent insights shed light on the global mechanisms involved in the abrupt oscillations of the Earth climate for the Late Glacial Maximum (LGM) to Holocene period (Zhang et al., 2014; Banderas et al., 2015). Yet the concomitant patterns of regional climate reorganization on continental areas are for now poorly documented. Particularly, few attempts have been made to propose temporal reconstructions of the regional climate variables in the High Tropical Andes, a region under the influence of multiple global climate forcings (Jomelli et al., 2014). We present new glacial chronologies from four sites of the Bolivian Altiplano: the Wara-Wara valley (17.3°S - 66.1°W), the Zongo valley (16.3°S - 68.1°W), the Cerro Tunupa (19.8°S - 67.6°W) and the Nevado Sajama (18.1°S 68.9°W). These chronologies are based on Cosmic Ray Exposure dating (CRE) from an exceptional suite of recessive moraines. These new data permitted to refine existing chronologies of Smith et al., 2005; Zech et al., 2010 and Blard et al., 2009. In both sites, glaciers recorded stillstand episodes synchronous with cold events such as the Henrich 1 event, the Younger Dryas and the Antarctic Cold Reversal. Since the nearby Altiplano basin registered lake level variations over the same period, we were able to apply a joint modelling of glaciers Equilibrium Line Altitude (ELA) and lake budget. This method permits to derive a temporal evolution of temperature and precipitation for the four sites. These new reconstructions show for all sites that glaciers of the Tropical Andes were influenced by the major climatic events of the Northern and Southern Hemispheres. Furthermore, the temperature variability observed at high latitudes results in these tropical latitudes in major precipitation variability whereas the lateglacial temperature patterns remain globally monotonic. This conversion of global temperature variability into regional precipitation variability support the idea that North Hemisphere cold events are coeval with an important southward deflexion of the Intertropical Convergence Zone (ITCZ) due to the inter-hemispheric temperature gradient (Schneider et al., 2014). Such a southward shift would lead to an increased moist supply of the subequatorial Amazonian basin (Montade et al., 2015) and thus an increased easterly driven moist transport over the Altiplano.

High resolution telescope and spectrograph observations of solar fine structure in the 1600 A region

NASA Technical Reports Server (NTRS)

Cook, J. W.; Brueckner, G. E.; Bartoe, J.-D. F.

1983-01-01

High spatial resolution spectroheliograms of the 1600 A region obtained during the HRTS rocket flight of 1978 February 13 are presented. The morphology, fine structure, and temporal behavior of emission bright points (BPs) in active and quiet regions are illustrated. In quiet regions, network elements persist as morphological units, although individual BPs may vary in intensity while usually lasting the flight duration. In cell centers, the BPs are highly variable on a 1 minute time scale. BPs in plages remain more constant in brightness over the observing sequence. BPs cover less than 4 percent of the quiet surface. The lifetime and degree of packing of BPs vary with the local strength of the magnetic field.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

2017-04-01

The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.

Temporal variability of selected air toxics in the United States

NASA Astrophysics Data System (ADS)

McCarthy, Michael C.; Hafner, Hilary R.; Chinkin, Lyle R.; Charrier, Jessica G.

Ambient measurements of hazardous air pollutants (HAPs, air toxics) collected in the United States from 1990 to 2005 were analyzed for diurnal, seasonal, and/or annual variability and trends. Visual and statistical analyses were used to identify and quantify temporal variations in air toxics at national and regional levels. Sufficient data were available to analyze diurnal variability for 14 air toxics, seasonal variability for 24 air toxics, and annual trends for 26 air toxics. Four diurnal variation patterns were identified and labeled invariant, nighttime peak, morning peak, and daytime peak. Three distinct seasonal patterns were identified and labeled invariant, cool, and warm. Multiple air toxics showed consistent decreasing trends over three trend periods, 1990-2005, 1995-2005, and 2000-2005. Trends appeared to be relatively consistent within chemically similar pollutant groups. Hydrocarbons such as benzene, 1,3-butadiene, styrene, xylene, and toluene decreased by approximately 5% or more per year at more than half of all monitoring sites. Concentrations of carbonyl compounds such as formaldehyde, acetaldehyde, and propionaldehyde were equally likely to have increased or decreased at monitoring sites. Chlorinated volatile organic compounds (VOCs) such as tetrachloroethylene, dichloromethane, and methyl chloroform decreased at more than half of all monitoring sites, but decreases among these species were much more variable than among the hydrocarbons. Lead particles decreased in concentration at most monitoring sites, but trends in other metals were not consistent over time.

Transport induced by mean-eddy interaction: II. Analysis of transport processes

NASA Astrophysics Data System (ADS)

Ide, Kayo; Wiggins, Stephen

2015-03-01

We present a framework for the analysis of transport processes resulting from the mean-eddy interaction in a flow. The framework is based on the Transport Induced by the Mean-Eddy Interaction (TIME) method presented in a companion paper (Ide and Wiggins, 2014) [1]. The TIME method estimates the (Lagrangian) transport across stationary (Eulerian) boundaries defined by chosen streamlines of the mean flow. Our framework proceeds after first carrying out a sequence of preparatory steps that link the flow dynamics to the transport processes. This includes the construction of the so-called "instantaneous flux" as the Hovmöller diagram. Transport processes are studied by linking the signals of the instantaneous flux field to the dynamical variability of the flow. This linkage also reveals how the variability of the flow contributes to the transport. The spatio-temporal analysis of the flux diagram can be used to assess the efficiency of the variability in transport processes. We apply the method to the double-gyre ocean circulation model in the situation where the Rossby-wave mode dominates the dynamic variability. The spatio-temporal analysis shows that the inter-gyre transport is controlled by the circulating eddy vortices in the fast eastward jet region, whereas the basin-scale Rossby waves have very little impact.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

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.

Data-adaptive harmonic analysis and prediction of sea level change in North Atlantic region

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2017-12-01

This study aims to characterize North Atlantic sea level variability across the temporal and spatial scales. We apply recently developed data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) stochastic modeling techniques [Chekroun and Kondrashov, 2017] to monthly 1993-2017 dataset of Combined TOPEX/Poseidon, Jason-1 and Jason-2/OSTM altimetry fields over North Atlantic region. The key numerical feature of the DAH relies on the eigendecomposition of a matrix constructed from time-lagged spatial cross-correlations. In particular, eigenmodes form an orthogonal set of oscillating data-adaptive harmonic modes (DAHMs) that come in pairs and in exact phase quadrature for a given temporal frequency. Furthermore, the pairs of data-adaptive harmonic coefficients (DAHCs), obtained by projecting the dataset onto associated DAHMs, can be very efficiently modeled by a universal parametric family of simple nonlinear stochastic models - coupled Stuart-Landau oscillators stacked per frequency, and synchronized across different frequencies by the stochastic forcing. Despite the short record of altimetry dataset, developed DAH-MSLM model provides for skillful prediction of key dynamical and statistical features of sea level variability. References M. D. Chekroun and D. Kondrashov, Data-adaptive harmonic spectra and multilayer Stuart-Landau models. HAL preprint, 2017, https://hal.archives-ouvertes.fr/hal-01537797

Temporal and spatial changes in social vulnerability to natural hazards

PubMed Central

Cutter, Susan L.; Finch, Christina

2008-01-01

During the past four decades (1960–2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades. PMID:18268336

Regional variability in sea ice melt in a changing Arctic.

PubMed

Perovich, Donald K; Richter-Menge, Jacqueline A

2015-07-13

In recent years, the Arctic sea ice cover has undergone a precipitous decline in summer extent. The sea ice mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean ice equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to ice losses in the Beaufort Sea, due to decreases in ice concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal trends from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea ice cover. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Evidence of Dynamic Crustal Deformation in Tohoku, Japan, From Time-Varying Receiver Functions

NASA Astrophysics Data System (ADS)

Porritt, R. W.; Yoshioka, S.

2017-10-01

Temporal variation of crustal structure is key to our understanding of Earth processes on human timescales. Often, we expect that the most significant structural variations are caused by strong ground shaking associated with large earthquakes, and recent studies seem to confirm this. Here we test the possibility of using P receiver functions (PRF) to isolate structural variations over time. Synthetic receiver function tests indicate that structural variation could produce PRF changes on the same order of magnitude as random noise or contamination by local earthquakes. Nonetheless, we find significant variability in observed receiver functions over time at several stations located in northeastern Honshu. Immediately following the Tohoku-oki earthquake, we observe high PRF variation clustering spatially, especially in two regions near the beginning and end of the rupture plane. Due to the depth sensitivity of PRF and the timescales over which this variability is observed, we infer this effect is primarily due to fluid migration in volcanic regions and shear stress/strength reorganization. While the noise levels in PRF are high for this type of analysis, by sampling small data sets, the computational cost is lower than other methods, such as ambient noise, thereby making PRF a useful tool for estimating temporal variations in crustal structure.

A method to assess the inter-annual weather-dependent variability in air pollution concentration and deposition based on weather typing

NASA Astrophysics Data System (ADS)

Pleijel, Håkan; Grundström, Maria; Karlsson, Gunilla Pihl; Karlsson, Per Erik; Chen, Deliang

2016-02-01

Annual anomalies in air pollutant concentrations, and deposition (bulk and throughfall) of sulphate, nitrate and ammonium, in the Gothenburg region, south-west Sweden, were correlated with optimized linear combinations of the yearly frequency of Lamb Weather Types (LWTs) to determine the extent to which the year-to-year variation in pollution exposure can be partly explained by weather related variability. Air concentrations of urban NO2, CO, PM10, as well as O3 at both an urban and a rural monitoring site, and the deposition of sulphate, nitrate and ammonium for the period 1997-2010 were included in the analysis. Linear detrending of the time series was performed to estimate trend-independent anomalies. These estimated anomalies were subtracted from observed annual values. Then the statistical significance of temporal trends with and without LWT adjustment was tested. For the pollutants studied, the annual anomaly was well correlated with the annual LWT combination (R2 in the range 0.52-0.90). Some negative (annual average [NO2], ammonia bulk deposition) or positive (average urban [O3]) temporal trends became statistically significant (p < 0.05) when the LWT adjustment was applied. In all the cases but one (NH4 throughfall, for which no temporal trend existed) the significance of temporal trends became stronger with LWT adjustment. For nitrate and ammonium, the LWT based adjustment explained a larger fraction of the inter-annual variation for bulk deposition than for throughfall. This is probably linked to the longer time scale of canopy related dry deposition processes influencing throughfall being explained to a lesser extent by LWTs than the meteorological factors controlling bulk deposition. The proposed novel methodology can be used by authorities responsible for air pollution management, and by researchers studying temporal trends in pollution, to evaluate e.g. the relative importance of changes in emissions and weather variability in annual air pollution exposure.

Variability and trends of local/regional scale surface climate in northern Africa during the twentieth century

NASA Astrophysics Data System (ADS)

Djomou, Zéphirin Yepdo; Monkam, David; Woafo, Paul

2014-08-01

Four regions are detected in northern Africa (20° W-40° E, 0-30° N) by applying the cluster analysis method on the annual rainfall anomalies of the period 1901-2000. The first region (R1), an arid land, covers essentially the north of 17.75° N from west to east of the study zone. The second region (R2), a semiarid land with a Sahelian climate, less warm than the dry climate of R1, is centred on Chad, with almost regular extension to the west towards Mauritania, and to the east, including the north of the Central African Republic and the Sudan. The region 3 (R3), a wet land, is centred on the Ivory Coast and covers totally Liberia, the south part of Ghana, Togo, Benin and the southwest of Nigeria. The fourth region (R4), corresponding to the wet equatorial forest, covers a part of Senegal, the Central Africa, the south of Sudan and a part of Ethiopia. An analysis of observed temperature and precipitation variability and trends throughout the twentieth century over these regions is presented. Summer, winter and annual data are examined using a range of variability measures. Statistically, significant warming trends are found over the majority of regions. The trends have a magnitude of up to 1.5 K per century. Only a few precipitation trends are statistically significant. Regional temperature and precipitation show pronounced variability at scales from interannual to multi-decadal. The interannual variability shows significant variations and trends throughout the century, the latter being mostly negative for precipitation and both positive and negative for temperature. Temperature and precipitation anomalies show a chaotic-type behaviour in which the regional conditions oscillate around the long-term mean trend and occasionally fall into long-lasting (up to 10 years or more) anomaly regimes. A generally modest temporal correlation is found between anomalies of different regions and between temperature and precipitation anomalies for the same region. This correlation is mostly positive for temperature in cases of adjacent regions. Several cases of negative interregional precipitation anomaly correlation are found. The El Niño Southern Oscillation significantly affects the anomaly variability patterns over a number of regions, mainly regions 3 (R3) and 4 (R4), while the North Atlantic Oscillation significantly affects the variability over arid and semiarid regions, R1 and R2.

Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity

PubMed Central

Takeuchi, Hikaru; Taki, Yasuyuki; Hashizume, Hiroshi; Sassa, Yuko; Nagase, Tomomi; Nouchi, Rui; Kawashima, Ryuta

2011-01-01

Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact subjects, resting brain activity (possibly underlain by default cognitive activity or metabolic demand from developed brain structures) is associated with cognitive functions. PMID:21980485

Monthly Rainfall Erosivity Assessment for Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation cover (C-factor) maps would enable the assessment of seasonal dynamics of erosion processes in Switzerland.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

PubMed

Duffy, Frank H; D'Angelo, Eugene; Rotenberg, Alexander; Gonzalez-Heydrich, Joseph

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences. CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Improving fire season definition by optimized temporal modelling of daily human-caused ignitions.

PubMed

Costafreda-Aumedes, S; Vega-Garcia, C; Comas, C

2018-07-01

Wildfire suppression management is usually based on fast control of all ignitions, especially in highly populated countries with pervasive values-at-risk. To minimize values-at-risk loss by improving response time of suppression resources it is necessary to anticipate ignitions, which are mainly caused by people. Previous studies have found that human-ignition patterns change spatially and temporally depending on socio-economic activities, hence, the deployment of suppression resources along the year should consider these patterns. However, full suppression capacity is operational only within legally established fire seasons, driven by past events and budgets, which limits response capacity and increases damages out of them. The aim of this study was to assess the temporal definition of fire seasons from the perspective of human-ignition patterns for the case study of Spain, where people cause over 95% of fires. Humans engage in activities that use fire as a tool in certain periods within a year, and in locations linked to specific spatial factors. Geographic variables (population, infrastructures, physiography and land uses) were used as explanatory variables for human-ignition patterns. The changing influence of these geographic variables on occurrence along the year was analysed with day-by-day logistic regression models. Daily models were built for all the municipal units in the two climatic regions in Spain (Atlantic and Mediterranean Spain) from 2002 to 2014, and similar models were grouped within continuous periods, designated as ignition-based seasons. We found three ignition-based seasons in the Mediterranean region and five in the Atlantic zones, not coincidental with calendar seasons, but with a high degree of agreement with current legally designated operational fire seasons. Our results suggest that an additional late-winter-early-spring fire season in the Mediterranean area and the extension of this same season in the Atlantic zone should be re-considered for operational purposes in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of time-varying tropospheric models on near-regional and regional infrasound propagation as constrained by observational data

NASA Astrophysics Data System (ADS)

McKenna, Mihan H.; Stump, Brian W.; Hayward, Chris

2008-06-01

The Chulwon Seismo-Acoustic Array (CHNAR) is a regional seismo-acoustic array with co-located seismometers and infrasound microphones on the Korean peninsula. Data from forty-two days over the course of a year between October 1999 and August 2000 were analyzed; 2052 infrasound-only arrivals and 23 seismo-acoustic arrivals were observed over the six week study period. A majority of the signals occur during local working hours, hour 0 to hour 9 UT and appear to be the result of cultural activity located within a 250 km radius. Atmospheric modeling is presented for four sample days during the study period, one in each of November, February, April, and August. Local meteorological data sampled at six hour intervals is needed to accurately model the observed arrivals and this data produced highly temporally variable thermal ducts that propagated infrasound signals within 250 km, matching the temporal variation in the observed arrivals. These ducts change dramatically on the order of hours, and meteorological data from the appropriate sampled time frame was necessary to interpret the observed arrivals.

Cortical Brain Atrophy and Intra-Individual Variability in Neuropsychological Test Performance in HIV Disease

PubMed Central

HINES, Lindsay J.; MILLER, Eric N.; HINKIN, Charles H.; ALGER, Jeffery R.; BARKER, Peter; GOODKIN, Karl; MARTIN, Eileen M.; MARUCA, Victoria; RAGIN, Ann; SACKTOR, Ned; SANDERS, Joanne; SELNES, Ola; BECKER, James T.

2015-01-01

Objective To characterize the relationship between dispersion-based intra-individual variability (IIVd) in neuropsychological test performance and brain volume among HIV seropositive and seronegative men and to determine the effects of cardiovascular risk and HIV infection on this relationship. Methods Magnetic Resonance Imaging (MRI) was used to acquire high-resolution neuroanatomic data from 147 men age 50 and over, including 80 HIV seropositive (HIV+) and 67 seronegative controls (HIV−) in this cross-sectional cohort study. Voxel Based Morphometry was used to derive volumetric measurements at the level of the individual voxel. These brain structure maps were analyzed using Statistical Parametric Mapping (SPM2). IIVd was measured by computing intra-individual standard deviations (ISD’s) from the standardized performance scores of five neuropsychological tests: Wechsler Memory Scale-III Visual Reproduction I and II, Logical Memory I and II, Wechsler Adult Intelligence Scale-III Letter Number Sequencing. Results Total gray matter (GM) volume was inversely associated with IIVd. Among all subjects, IIVd -related GM atrophy was observed primarily in: 1) the inferior frontal gyrus bilaterally, the left inferior temporal gyrus extending to the supramarginal gyrus, spanning the lateral sulcus; 2) the right superior parietal lobule and intraparietal sulcus; and, 3) dorsal/ventral regions of the posterior section of the transverse temporal gyrus. HIV status, biological, and cardiovascular disease (CVD) variables were not linked to IIVd -related GM atrophy. Conclusions IIVd in neuropsychological test performance may be a sensitive marker of cortical integrity in older adults, regardless of HIV infection status or CVD risk factors, and degree of intra-individual variability links with volume loss in specific cortical regions; independent of mean-level performance on neuropsychological tests. PMID:26303224

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

NASA Astrophysics Data System (ADS)

Tréguer, Paul; Goberville, Eric; Barrier, Nicolas; L'Helguen, Stéphane; Morin, Pascal; Bozec, Yann; Rimmelin-Maury, Peggy; Czamanski, Marie; Grossteffan, Emilie; Cariou, Thierry; Répécaud, Michel; Quéméner, Loic

2014-11-01

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998-2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

Hydrological signals in height and gravity in northeastern Italy inferred from principal components analysis

NASA Astrophysics Data System (ADS)

Zerbini, S.; Raicich, F.; Richter, B.; Gorini, V.; Errico, M.

2010-04-01

This work describes a study of GPS heights, gravity and hydrological time series collected by stations located in northeastern Italy. During the last 12 years, changes in the long-term behaviors of the GPS heights and gravity time series are observed. In particular, starting in 2004-2005, a height increase is observed over the whole area. The temporal and spatial variability of these parameters has been studied as well as those of key hydrological variables, namely precipitation, hydrological balance and water table by using the Empirical Orthogonal Functions (EOF) analysis. The coupled variability between the GPS heights and the hydrological balance and precipitation data has been investigated by means of the Singular Value Decomposition (SVD) approach. Significant common patterns in the spatial and temporal variability of these parameters have been recognized. In particular, hydrology-induced variations are clearly observable starting in 2002-2003 in the southern part of the Po Plain for the longest time series, and from 2004-2005 over the whole area. These findings, obtained by means of purely mathematical approaches, are supported by sound physical interpretation suggesting that the climate-related fluctuations in the regional/local hydrological regime are one of the main contributors to the observed variations. A regional scale signal has been identified in the GPS station heights; it is characterized by the opposite behavior of the southern and northern stations in response to the hydrological forcing. At Medicina, in the southern Po Plain, the EOF analysis has shown a marked common signal between the GPS heights and the Superconducting Gravimeter (SG) data both over the long and the short period.

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

NASA Astrophysics Data System (ADS)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Nino in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.

Spatio-Temporal Variability of the Phase of Total Ozone Quasi-Decennial Oscillations

NASA Astrophysics Data System (ADS)

Visheratin, K. N.

2017-12-01

The SBUV/SBUV2 (65° S-65° N) and Bodeker Scientific (90° S-90° N) satellite databases have been used for composite and cross-wavelet analyses of the spatio-temporal variability of phase relations between a 11-year cycle of solar activity (SA) and quasi-decennial oscillations (QDOs) of total ozone content (TOC). For globally average TOC values, the QDO maxima coincide in phase with the solar-activity maxima, and amplitude variations of TOC correlate with those of the 11-year solar cycle. According to the analysis of amplitude and phase of QDOs for the zonal average TOC fields, a QDO amplitude is about 6-7 Dobson Units (DU) in the high northern and southern latitudes, and it does not exceed 2-3 DU in the tropic regions. The latitudinal TOC variations are distinguished by a delay of the quasi-decennial oscillation phase in the southern latitudes in comparison with the northern latitudes. The TOC maxima phase coincides with the SA maxima phase in the tropic regions; the TOC variations go ahead of the SA variations, on average, in moderate and high latitudes of the Northern Hemisphere; the TOC variations are behind the SA variations in the Southern Hemisphere. The phase delay between TOC QDO maxima in the northern and southern latitudes appears to increase in the course of time, and the TOC quasi-decennial variations in the Arctic and Antarctic subpolar regions occur approximately in an antiphase over the last two decades.

Sampling of the Diurnal Cycle of Precipitation using TRMM

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Bell, Thomas L.; Xu, Li-Ming; Starr, David OC. (Technical Monitor)

2001-01-01

We examine the temporal sampling of tropical regions using observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR). We conclude that PR estimates at any one hour, even using three years of data, are inadequate to describe the diurnal cycle of precipitation over regions smaller than 12 degrees, due to high spatial variability in sampling. We show that the optimum period of accumulation is four hours. Diurnal signatures display half as much sampling error when averaged over four hours of local time. A similar pattern of sampling variability is found in the TMI data, despite the TMI's wider swath and increased sampling. These results are verified using an orbital model. The sensitivity of the sampling to satellite altitude is presented, as well as sampling patterns at the new TRMM altitude of 402.5 km.

Evaluating Urban Methane Emissions with a Light Rail Vehicle Platform in Salt Lake City, UT

NASA Astrophysics Data System (ADS)

Mitchell, L.; Fasoli, B.; Crosman, E.; Lin, J. C.; Bowling, D. R.; Ehleringer, J. R.

2016-12-01

Urban environments are characterized by both spatial complexity and temporal variability, each of which present challenges for measurement strategies aimed at constraining estimates of greenhouse gas emissions and air quality. To address these challenges we initiated a project in December 2014 to measure trace species (CO2, CH4, O3, and Particulate Matter) by way of a Utah Transit Authority (UTA) electricity-powered light rail vehicle whose route traverses the metropolitan Salt Lake Valley in Utah, USA on an hourly basis, retracing the same route through commercial, residential, suburban, and rural typologies. Light rail vehicles present advantages as a measurement platform, including the absence of in-situ fossil fuel emissions, regular repeated transects across an urban region that provide both spatial and temporal information, and relatively low operating costs. We will present initial results investigating methane point sources and evaluating the magnitude and temporal characteristics of these emissions.

Chronic radiation exposure modifies temporal dynamics of cytogenetic but not reproductive indicators in Scots pine populations.

PubMed

Geras'kin, Stanislav; Oudalova, Alla; Kuzmenkov, Alexey; Vasiliyev, Denis

2018-04-18

Over a period of 13 years (2003-2015), reproductive and cytogenetic effects are investigated in Scots pine populations growing in the Bryansk region of Russia radioactively contaminated as a result of the Chernobyl accident. In reference populations, the frequencies of cytogenetic abnormalities are shown to change with time in a cyclic manner. In chronically exposed populations, the cyclic patterns in temporal dynamics of cytogenetic abnormalities appear to be disturbed. In addition, a tendency to decrease in the frequencies of cytogenetic abnormalities with time as well as an increase in their variability with dose rate is revealed. In contrast, no significant impact of chronic radiation exposure on the time dynamics of reproductive indexes is detected. Finally, long-term observations on chronically exposed Scots pine populations revealed qualitative differences in the temporal dynamics of reproductive and cytogenetic indicators. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

Wikle, C.K.; Royle, J. Andrew

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries.

PubMed

Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B

2013-01-29

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries

PubMed Central

Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.

2013-01-01

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

A Combined Study of Photospheric Magnetic and Current Helicities and Subsurface Kinetic Helicities of Solar Active Regions during 2006-2012

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Petrie, G.; Komm, R.

2014-01-01

We compare the average photospheric current helicity H_c, photospheric twist parameter α (a well-known proxy for the full relative magnetic helicity), and subsurface kinetic helicity K_h for 128 active regions observed between 2006-2012. We use 1436 Hinode photospheric vector magnetograms and subsurface fluid velocity data from GONG Dopplergrams. We find a significant hemispheric bias in all three parameters. The K_h parameter is preferentially positive/negative in the southern/northern hemisphere. The H_c and α parameters have the same bias for strong fields |{B}|>1000 G). We examine the temporal variability of each parameter for each active region and identify a significant subset of regions whose three helicity parameters all exhibit clear increasing or decreasing trends. The temporal profiles of these regions have the same bias: positive/negative helicity in the northern/southern hemisphere. The results are consistent with Longcope et al.'s Σ-effect. This work is carried out through the National Solar Observatory Research Experiences for Undergraduate (REU) site program, which is co-funded by the Department of Defense in partnership with the NSF REU Program. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy, Inc. (AURA) under cooperative agreement with the National Science Foundation.

Acoustic wave propagation in a temporal evolving shear-layer for low-Mach number perturbations

NASA Astrophysics Data System (ADS)

Hau, Jan-Niklas; Müller, Björn

2018-01-01

We study wave packets with the small perturbation/gradient Mach number interacting with a smooth shear-layer in the linear regime of small amplitude perturbations. In particular, we investigate the temporal evolution of wave packets in shear-layers with locally curved regions of variable size using non-modal linear analysis and direct numerical simulations of the two-dimensional gas-dynamical equations. Depending on the wavenumber of the initially imposed wave packet, three different types of behavior are observed: (i) The wave packet passes through the shear-layer and constantly transfers energy back to the mean flow. (ii) It is turned around (or reflected) within the sheared region and extracts energy from the base flow. (iii) It is split into two oppositely propagating packages when reaching the upper boundary of the linearly sheared region. The conducted direct numerical simulations confirm that non-modal linear stability analysis is able to predict the wave packet dynamics, even in the presence of non-linearly sheared regions. In the light of existing studies in this area, we conclude that the sheared regions are responsible for the highly directed propagation of linearly generated acoustic waves when there is a dominating source, as it is the case for jet flows.

Spatiotemporal drought variability of the eastern Tibetan Plateau during the last millennium

NASA Astrophysics Data System (ADS)

Deng, Yang; Gou, Xiaohua; Gao, Linlin; Yang, Meixue; Zhang, Fen

2017-09-01

Tibetan Plateau is the headwater region of many major Asian rivers and very susceptive to climate change. Therefore, knowledge about climate and its spatiotemporal variability in this area is very important for ecological conservation, water resource management and social development. The aim of this study was to reconstruct and analyze the hydroclimate variation on eastern Tibetan Plateau (ETP) over many centuries and explore possible forcing factors on regional hydroclimate variability. We used 118 tree-ring chronologies from ETP to reconstruct the gridded May-July Standardized Precipitation Evapotranspiration Index for the ETP over the last millennium. The reconstruction was developed using an ensemble point-by-point reconstruction method, and a searching region method was used to locate the candidate tree-ring chronologies. The reconstructions have nicely captured the spatial and temporal features of the regional drought variation. The drought variations in south and north of 32.5°N are notably different, which may be related to the divergence influence of North Atlantic Oscillation on the climate systems in the south and north, as well as differences in local climate. Spectral analysis and series comparison suggest that the drought variation in the northeastern Tibetan Plateau has been possibly influenced by solar activity on centurial and longer time scale.

Productivity in the barents sea--response to recent climate variability.

PubMed

Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.

Productivity in the Barents Sea - Response to Recent Climate Variability

PubMed Central

Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513

Regional contribution to variability and trends of global gross primary productivity

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

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less

Regional contribution to variability and trends of global gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.; Bond-Lamberty, Ben; Ciais, Philippe; Zhao, Fang; Reyer, Christopher P. O.; Ostberg, Sebastian; Chang, Jinfeng; Ito, Akihiko; Yang, Jia; Zeng, Ning; Kalnay, Eugenia; West, Tristram; Leng, Guoyong; Francois, Louis; Munhoven, Guy; Henrot, Alexandra; Tian, Hanqin; Pan, Shufen; Nishina, Kazuya; Viovy, Nicolas; Morfopoulos, Catherine; Betts, Richard; Schaphoff, Sibyll; Steinkamp, Jörg; Hickler, Thomas

2017-10-01

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr-1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

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

PubMed Central

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

2012-01-01

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

Are there meaningful individual differences in temporal inconsistency in self-reported personality?

PubMed

Soubelet, Andrea; Salthouse, Timothy A; Oishi, Shigehiro

2014-11-01

The current project had three goals. The first was to examine whether it is meaningful to refer to across-time variability in self-reported personality as an individual differences characteristic. The second was to investigate whether negative affect was associated with variability in self-reported personality, while controlling for mean levels, and correcting for measurement errors. The third goal was to examine whether variability in self-reported personality would be larger among young adults than among older adults, and whether the relation of variability with negative affect would be stronger at older ages than at younger ages. Two moderately large samples of participants completed the International Item Pool Personality questionnaire assessing the Big Five personality dimensions either twice or thrice, in addition to several measures of negative affect. Results were consistent with the hypothesis that within-person variability in self-reported personality is a meaningful individual difference characteristic. Some people exhibited greater across-time variability than others after removing measurement error, and people who showed temporal instability in one trait also exhibited temporal instability across the other four traits. However, temporal variability was not related to negative affect, and there was no evidence that either temporal variability or its association with negative affect varied with age.

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

RMS Spectral Modelling - a powerful tool to probe the origin of variability in Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Mallick, Labani; Dewangan, Gulab chand; Misra, Ranjeev

2016-07-01

The broadband energy spectra of Active Galactic Nuclei (AGN) are very complex in nature with the contribution from many ingredients: accretion disk, corona, jets, broad-line region (BLR), narrow-line region (NLR) and Compton-thick absorbing cloud or TORUS. The complexity of the broadband AGN spectra gives rise to mean spectral model degeneracy, e.g, there are competing models for the broad feature near 5-7 keV in terms of blurred reflection and complex absorption. In order to overcome the energy spectral model degeneracy, the most reliable approach is to study the RMS variability spectrum which connects the energy spectrum with temporal variability. The origin of variability could be pivoting of the primary continuum, reflection and/or absorption. The study of RMS (Root Mean Square) spectra would help us to connect the energy spectra with the variability. In this work, we study the energy dependent variability of AGN by developing theoretical RMS spectral model in ISIS (Interactive Spectral Interpretation System) for different input energy spectra. In this talk, I would like to present results of RMS spectral modelling for few radio-loud and radio-quiet AGN observed by XMM-Newton, Suzaku, NuSTAR and ASTROSAT and will probe the dichotomy between these two classes of AGN.

Southern Hemisphere rainfall variability over the past 200 years

NASA Astrophysics Data System (ADS)

Gergis, Joëlle; Henley, Benjamin J.

2017-04-01

This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall-climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

Seasonal induced changes in spinach rhizosphere microbial community structure with varying salinity and drought.

PubMed

Mark Ibekwe, A; Ors, Selda; Ferreira, Jorge F S; Liu, Xuan; Suarez, Donald L

2017-02-01

Salinity is a common problem under irrigated agriculture, especially in low rainfall and high evaporative demand areas of southwestern United States and other semi-arid regions around the world. However, studies on salinity effects on soil microbial communities are relatively few while the effects of irrigation-induced salinity on soil chemical and physical properties and plant growth are well documented. In this study, we examined the effects of salinity, temperature, and temporal variability on soil and rhizosphere microbial communities in sand tanks irrigated with prepared solutions designed to simulate saline wastewater. Three sets of experiments with spinach (Spinacia oleracea L., cv. Racoon) were conducted under saline water during different time periods (early winter, late spring, and early summer). Bacterial 16S V4 rDNA region was amplified utilizing fusion primers designed against the surrounding conserved regions using MiSeq® Illumina sequencing platform. Across the two sample types, bacteria were relatively dominant among three phyla-the Proteobacteria, Cyanobacteria, and Bacteroidetes-accounted for 77.1% of taxa detected in the rhizosphere, while Proteobacteria, Bacteroidetes, and Actinobacteria accounted for 55.1% of taxa detected in soil. The results were analyzed using UniFrac coupled with principal coordinate analysis (PCoA) to compare diversity, abundance, community structure, and specific bacterial groups in soil and rhizosphere samples. Permutational analysis of variance (PERMANOVA) analysis showed that soil temperature (P=0.001), rhizosphere temperature (P=0.001), rhizosphere salinity (P=0.032), and evapotranspiration (P=0.002) significantly affected beta diversity of soil and rhizosphere microbial communities. Furthermore, salinity had marginal effects (P=0.078) on soil beta diversity. However, temporal variability differentially affected rhizosphere microbial communities irrigated with saline wastewater. Therefore, microbial communities in soils impacted by saline irrigation water respond differently to irrigation water quality and season of application due to temporal effects associated with temperature. Published by Elsevier B.V.

Temporal and Regional Variability in the Skin Microbiome of Humpback Whales along the Western Antarctic Peninsula.

PubMed

Bierlich, K C; Miller, Carolyn; DeForce, Emelia; Friedlaender, Ari S; Johnston, David W; Apprill, Amy

2018-03-01

The skin is the first line of defense between an animal and its environment, and disruptions in skin-associated microorganisms can be linked to an animal's health and nutritional state. To better understand the skin microbiome of large whales, high-throughput sequencing of partial small subunit rRNA genes was used to study the skin-associated bacteria of 89 seemingly healthy humpback whales ( Megaptera novaeangliae ) sampled along the Western Antarctic Peninsula (WAP) during early (2010) and late (2013) austral summers. Six core groups of bacteria were present in 93% or more of all humpback skin samples. A shift was observed in the average relative abundances of these core bacteria over time, with the emergence of four additional core groups of bacteria that corresponded to a decrease in water temperature, possibly caused by season- or foraging-related changes in skin biochemistry that influenced microbial growth, or other temporal factors. The skin microbiome differed between whales sampled at several regional locations along the WAP, suggesting that environmental factors or population may also influence the whale skin microbiome. Overall, the skin microbiome of humpback whales appears to provide insight into animal- and environment-related factors and may serve as a useful indicator for animal health or ecosystem alterations. IMPORTANCE The microbiomes of wild animals are currently understudied but may provide information about animal health and/or animal-environment interactions. In the largest sampling of any marine mammal microbiome, this study demonstrates conservation in the skin microbiome of 89 seemingly healthy humpback whales sampled in the Western Antarctic Peninsula, with shifts in the bacterial community composition related to temporal and regional variability. This study is important because it suggests that the skin microbiome of humpback whales could provide insight into animal nutritional or seasonal/environment-related factors, which are becoming increasingly important to recognize due to unprecedented rates of climate change and anthropogenic impact on ocean ecosystems. Copyright © 2018 Bierlich et al.

Temporal and Regional Variability in the Skin Microbiome of Humpback Whales along the Western Antarctic Peninsula

PubMed Central

Bierlich, K. C.; Miller, Carolyn; DeForce, Emelia; Friedlaender, Ari S.

2017-01-01

ABSTRACT The skin is the first line of defense between an animal and its environment, and disruptions in skin-associated microorganisms can be linked to an animal's health and nutritional state. To better understand the skin microbiome of large whales, high-throughput sequencing of partial small subunit rRNA genes was used to study the skin-associated bacteria of 89 seemingly healthy humpback whales (Megaptera novaeangliae) sampled along the Western Antarctic Peninsula (WAP) during early (2010) and late (2013) austral summers. Six core groups of bacteria were present in 93% or more of all humpback skin samples. A shift was observed in the average relative abundances of these core bacteria over time, with the emergence of four additional core groups of bacteria that corresponded to a decrease in water temperature, possibly caused by season- or foraging-related changes in skin biochemistry that influenced microbial growth, or other temporal factors. The skin microbiome differed between whales sampled at several regional locations along the WAP, suggesting that environmental factors or population may also influence the whale skin microbiome. Overall, the skin microbiome of humpback whales appears to provide insight into animal- and environment-related factors and may serve as a useful indicator for animal health or ecosystem alterations. IMPORTANCE The microbiomes of wild animals are currently understudied but may provide information about animal health and/or animal-environment interactions. In the largest sampling of any marine mammal microbiome, this study demonstrates conservation in the skin microbiome of 89 seemingly healthy humpback whales sampled in the Western Antarctic Peninsula, with shifts in the bacterial community composition related to temporal and regional variability. This study is important because it suggests that the skin microbiome of humpback whales could provide insight into animal nutritional or seasonal/environment-related factors, which are becoming increasingly important to recognize due to unprecedented rates of climate change and anthropogenic impact on ocean ecosystems. PMID:29269499

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

NASA Astrophysics Data System (ADS)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields and thus has potential to be used for yield prediction, or for ingestion into a crop simulation model as a crop-specific moisture stress function.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

Bacterial and Archaeal Communities Variability Associated with Upwelling and Anthropogenic Pressures in the Protection Area of Arraial do Cabo (Cabo Frio region - RJ).

PubMed

Coelho-Souza, Sergio A; Araújo, Fábio V; Cury, Juliano C; Jesus, Hugo E; Pereira, Gilberto C; Guimarães, Jean R D; Peixoto, Raquel S; Dávila, Alberto M R; Rosado, Alexandre S

2015-09-01

Upwelling systems contain a high diversity of pelagic microorganisms and their composition and activity are defined by factors like temperature and nutrient concentration. Denaturing gradient gel electrophoresis (DGGE) technique was used to verify the spatial and temporal genetic variability of Bacteria and Archaea in two stations of the Arraial do Cabo coastal region, one under upwelling pressure and another under anthropogenic pressure. In addition, biotic and abiotic variables were measured in surface and deep waters from three other stations between these stations. Six samplings were done during a year and adequately represented the degrees of upwelling and anthropogenic pressures to the system. Principal Component Analysis (PCA) showed negative correlations between the concentrations of ammonia and phosphorous with prokaryotic secondary production and the total heterotrophic bacteria. PCA also showed negative correlation between temperature and the abundance of prokaryotic cells. Bacterial and archaeal compositions were changeable as were the oceanographic conditions, and upwelling had a regional pressure while anthropogenic pressure was punctual. We suggest that the measurement of prokaryotic secondary production was associated with both Bacteria and Archaea activities, and that substrate availability and temperature determine nutrients cycling.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

Spatial and temporal variation of sources contributing to quasi-ultrafine particulate matter PM0.36 in Augsburg, Germany.

PubMed

Li, Fengxia; Schnelle-Kreis, Jürgen; Cyrys, Josef; Wolf, Kathrin; Karg, Erwin; Gu, Jianwei; Orasche, Jürgen; Abbaszade, Gülcin; Peters, Annette; Zimmermann, Ralf

2018-08-01

to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources. 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions. 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby. temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP. Copyright © 2018 Elsevier B.V. All rights reserved.

Subtropical Gyre Variability Observed by Ocean Color Satellites

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Signorini, Sergio R.; Christian, James R.

2002-01-01

The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 - June 1997) of OCTS and nearly 5 years (September 1997 - June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

Sea ice and oceanic processes on the Ross Sea continental shelf

NASA Technical Reports Server (NTRS)

Jacobs, S. S.; Comiso, J. C.

1989-01-01

The spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf have been investigated in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86 percent during winter with little month-to-month of interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn.

A role for ocean biota in tropical intraseasonal atmospheric variability

NASA Astrophysics Data System (ADS)

Gildor, Hezi; Sobel, Adam H.; Cane, Mark A.; Sambrotto, Raymond N.

2003-05-01

We propose that temporal variations within the marine plankton system can induce intraseasonal variations in sea surface temperature (SST) through the effect on solar penetration due to chlorophyll and other optically active organic components. Sensitivity studies with a simple model suggest that these small oscillations in SST may stimulate radiative-convective oscillations in the atmosphere which amplify them and thus induce or modulate significant variability in the coupled system. Long term bio-optical measurements in the Western Pacific, where satellite time series are degraded by clouds, would provide a test of our theory and would improve our understanding of the heat balance in this climatically important region.

From AWE-GEN to AWE-GEN-2d: a high spatial and temporal resolution weather generator

NASA Astrophysics Data System (ADS)

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

2016-04-01

A new weather generator, AWE-GEN-2d (Advanced WEather GENerator for 2-Dimension grid) is developed following the philosophy of combining physical and stochastic approaches to simulate meteorological variables at high spatial and temporal resolution (e.g. 2 km x 2 km and 5 min for precipitation and cloud cover and 100 m x 100 m and 1 h for other variables variable (temperature, solar radiation, vapor pressure, atmospheric pressure and near-surface wind). The model is suitable to investigate the impacts of climate variability, temporal and spatial resolutions of forcing on hydrological, ecological, agricultural and geomorphological impacts studies. Using appropriate parameterization the model can be used in the context of climate change. Here we present the model technical structure of AWE-GEN-2d, which is a substantial evolution of four preceding models (i) the hourly-point scale Advanced WEather GENerator (AWE-GEN) presented by Fatichi et al. (2011, Adv. Water Resour.) (ii) the Space-Time Realizations of Areal Precipitation (STREAP) model introduced by Paschalis et al. (2013, Water Resour. Res.), (iii) the High-Resolution Synoptically conditioned Weather Generator developed by Peleg and Morin (2014, Water Resour. Res.), and (iv) the Wind-field Interpolation by Non Divergent Schemes presented by Burlando et al. (2007, Boundary-Layer Meteorol.). The AWE-GEN-2d is relatively parsimonious in terms of computational demand and allows generating many stochastic realizations of current and projected climates in an efficient way. An example of model application and testing is presented with reference to a case study in the Wallis region, a complex orography terrain in the Swiss Alps.

Hydrometeorological daily recharge assessment model (DREAM) for the Western Mountain Aquifer, Israel: Model application and effects of temporal patterns

NASA Astrophysics Data System (ADS)

Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Navon, S.; Frumkin, A.; Morin, E.

2010-05-01

Recharge is a critical issue for water management. Recharge assessment and the factors affecting recharge are of scientific and practical importance. The purpose of this study was to develop a daily recharge assessment model (DREAM) on the basis of a water balance principle with input from conventional and generally available precipitation and evaporation data and demonstrate the application of this model to recharge estimation in the Western Mountain Aquifer (WMA) in Israel. The WMA (area 13,000 km2) is a karst aquifer that supplies 360-400 Mm3 yr-1 of freshwater, which constitutes 20% of Israel's freshwater and is highly vulnerable to climate variability and change. DREAM was linked to a groundwater flow model (FEFLOW) to simulate monthly hydraulic heads and spring flows. The models were calibrated for 1987-2002 and validated for 2003-2007, yielding high agreement between calculated and measured values (R2 = 0.95; relative root-mean-square error = 4.8%; relative bias = 1.04). DREAM allows insights into the effect of intra-annual precipitation distribution factors on recharge. Although annual precipitation amount explains ˜70% of the variability in simulated recharge, analyses with DREAM indicate that the rainy season length is an important factor controlling recharge. Years with similar annual precipitation produce different recharge values as a result of temporal distribution throughout the rainy season. An experiment with a synthetic data set exhibits similar results, explaining ˜90% of the recharge variability. DREAM represents significant improvement over previous recharge estimation techniques in this region by providing near-real-time recharge estimates that can be used to predict the impact of climate variability on groundwater resources at high temporal and spatial resolution.

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

USGS Publications Warehouse

Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad

2013-01-01

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Dynamics of particulate organic matter composition in coastal systems: Forcing of spatio-temporal variability at multi-systems scale

NASA Astrophysics Data System (ADS)

Liénart, Camilla; Savoye, Nicolas; David, Valérie; Ramond, Pierre; Rodriguez Tress, Paco; Hanquiez, Vincent; Marieu, Vincent; Aubert, Fabien; Aubin, Sébastien; Bichon, Sabrina; Boinet, Christophe; Bourasseau, Line; Bozec, Yann; Bréret, Martine; Breton, Elsa; Caparros, Jocelyne; Cariou, Thierry; Claquin, Pascal; Conan, Pascal; Corre, Anne-Marie; Costes, Laurence; Crouvoisier, Muriel; Del Amo, Yolanda; Derriennic, Hervé; Dindinaud, François; Duran, Robert; Durozier, Maïa; Devesa, Jérémy; Ferreira, Sophie; Feunteun, Eric; Garcia, Nicole; Geslin, Sandrine; Grossteffan, Emilie; Gueux, Aurore; Guillaudeau, Julien; Guillou, Gaël; Jolly, Orianne; Lachaussée, Nicolas; Lafont, Michel; Lagadec, Véronique; Lamoureux, Jézabel; Lauga, Béatrice; Lebreton, Benoît; Lecuyer, Eric; Lehodey, Jean-Paul; Leroux, Cédric; L'Helguen, Stéphane; Macé, Eric; Maria, Eric; Mousseau, Laure; Nowaczyk, Antoine; Pineau, Philippe; Petit, Franck; Pujo-Pay, Mireille; Raimbault, Patrick; Rimmelin-Maury, Peggy; Rouaud, Vanessa; Sauriau, Pierre-Guy; Sultan, Emmanuelle; Susperregui, Nicolas

2018-03-01

In costal systems, particulate organic matter (POM) results from a multiplicity of sources having their respective dynamics in terms of production, decomposition, transport and burial. The POM pool experiences thus considerable spatial and temporal variability. In order to better understand this variability, the present study employs statistical multivariate analyses to investigate links between POM composition and environmental forcings for a panel of twelve coastal systems distributed along the three maritime regions of France and monitored weekly to monthly for 1 to 8 years. At multi-system scale, two main gradients of POC composition have been identified: a 'Continent-Ocean' gradient associated with hydrodynamics, sedimentary dynamics and depth of the water column, and a gradient of trophic status related to nutrient availability. At local scale, seasonality of POC composition appears to be station-specific but still related to part of the above-mentioned forcings. A typology of systems was established by coupling spatial and temporal variability of POC composition. Four groups were highlighted: (1) the estuarine stations where POC composition is dominated by terrestrial POM and driven by hydrodynamics and sedimentary processes, (2) the oligotrophic systems, characterized by the contribution of diazotrophs due to low nutrient availability, and the marine meso/eutroph systems whose POC composition is (3) either deeply dominated by phytoplankton or (4) dominated by phytoplankton but where the contribution of continental and benthic POC is not negligible and is driven by hydrodynamics, sedimentary processes and the height of the water column. Finally, the present study provides several insights into the different forcings to POM composition and dynamics in temperate coastal systems at local and multi-system scales. This work also presents a methodological approach that establishes statistical links between forcings and POM composition, helping to gain more objectively insight of forcings.

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

Observing large-scale temporal variability of ocean currents by satellite altimetry - With application to the Antarctic circumpolar current

NASA Technical Reports Server (NTRS)

Fu, L.-L.; Chelton, D. B.

1985-01-01

A new method is developed for studying large-scale temporal variability of ocean currents from satellite altimetric sea level measurements at intersections (crossovers) of ascending and descending orbit ground tracks. Using this method, sea level time series can be constructed from crossover sea level differences in small sample areas where altimetric crossovers are clustered. The method is applied to Seasat altimeter data to study the temporal evolution of the Antarctic Circumpolar Current (ACC) over the 3-month Seasat mission (July-October 1978). The results reveal a generally eastward acceleration of the ACC around the Southern Ocean with meridional disturbances which appear to be associated with bottom topographic features. This is the first direct observational evidence for large-scale coherence in the temporal variability of the ACC. It demonstrates the great potential of satellite altimetry for synoptic observation of temporal variability of the world ocean circulation.

The need to consider temporal variability when modelling exchange at the sediment-water interface

USGS Publications Warehouse

Rosenberry, Donald O.

2011-01-01

Most conceptual or numerical models of flows and processes at the sediment-water interface assume steady-state conditions and do not consider temporal variability. The steady-state assumption is required because temporal variability, if quantified at all, is usually determined on a seasonal or inter-annual scale. In order to design models that can incorporate finer-scale temporal resolution we first need to measure variability at a finer scale. Automated seepage meters that can measure flow across the sediment-water interface with temporal resolution of seconds to minutes were used in a variety of settings to characterize seepage response to rainfall, wind, and evapotranspiration. Results indicate that instantaneous seepage fluxes can be much larger than values commonly reported in the literature, although seepage does not always respond to hydrological processes. Additional study is needed to understand the reasons for the wide range and types of responses to these hydrologic and atmospheric events.

Observing spatio-temporal dynamics of excitable media using reservoir computing

NASA Astrophysics Data System (ADS)

Zimmermann, Roland S.; Parlitz, Ulrich

2018-04-01

We present a dynamical observer for two dimensional partial differential equation models describing excitable media, where the required cross prediction from observed time series to not measured state variables is provided by Echo State Networks receiving input from local regions in space, only. The efficacy of this approach is demonstrated for (noisy) data from a (cubic) Barkley model and the Bueno-Orovio-Cherry-Fenton model describing chaotic electrical wave propagation in cardiac tissue.

Response of Bacterioplankton Communities to Cadmium Exposure in Coastal Water Microcosms with High Temporal Variability

PubMed Central

Wang, Kai; Xiong, Jinbo; Chen, Xinxin; Zheng, Jialai; Hu, Changju; Yang, Yina; Zhu, Jianlin

2014-01-01

Multiple anthropogenic disturbances to bacterial diversity have been investigated in coastal ecosystems, in which temporal variability in the bacterioplankton community has been considered a ubiquitous process. However, far less is known about the temporal dynamics of a bacterioplankton community responding to pollution disturbances such as toxic metals. We used coastal water microcosms perturbed with 0, 10, 100, and 1,000 μg liter−1 of cadmium (Cd) for 2 weeks to investigate temporal variability, Cd-induced patterns, and their interaction in the coastal bacterioplankton community and to reveal whether the bacterial community structure would reflect the Cd gradient in a temporally varying system. Our results showed that the bacterioplankton community structure shifted along the Cd gradient consistently after a 4-day incubation, although it exhibited some resistance to Cd at low concentration (10 μg liter−1). A process akin to an arms race between temporal variability and Cd exposure was observed, and the temporal variability overwhelmed Cd-induced patterns in the bacterial community. The temporal succession of the bacterial community was correlated with pH, dissolved oxygen, NO3−-N, NO2−-N, PO43−-P, dissolved organic carbon, and chlorophyll a, and each of these parameters contributed more to community variance than Cd did. However, elevated Cd levels did decrease the temporal turnover rate of community. Furthermore, key taxa, affiliated to the families Flavobacteriaceae, Rhodobacteraceae, Erythrobacteraceae, Piscirickettsiaceae, and Alteromonadaceae, showed a high frequency of being associated with Cd levels during 2 weeks. This study provides direct evidence that specific Cd-induced patterns in bacterioplankton communities exist in highly varying manipulated coastal systems. Future investigations on an ecosystem scale across longer temporal scales are needed to validate the observed pattern. PMID:25326310

Aerosol direct effect on solar radiation over the eastern Mediterranean Sea based on AVHRR satellite measurements

NASA Astrophysics Data System (ADS)

Georgakaki, Paraskevi; Papadimas, Christos D.; Hatzianastassiou, Nikos; Fotiadi, Aggeliki; Matsoukas, Christos; Stackhouse, Paul; Kanakidou, Maria; Vardavas, Ilias M.

2017-04-01

Despite the improved scientific understanding of the direct effect of aerosols on solar radiation (direct radiative effect, DRE) improvements are necessary, for example regarding the accuracy of the magnitude of estimated DREs and their spatial and temporal variability. This variability cannot be ensured by in-situ surface and airborne measurements, while it is also relatively difficult to capture through satellite observations. This becomes even more difficult when complete spatial coverage of extended areas is required, especially concerning areas that host various aerosol types with variable physico-chemical and optical aerosol properties. Better assessments of aerosol DREs are necessary, relying on aerosol optical properties with high spatial and temporal variation. The present study aims to provide a refined, along these lines, assessment of aerosol DREs over the eastern Mediterranean (EM) Sea, which is a key area for aerosol studies. Daily DREs are computed for 1˚ x1˚ latitude-longitude grids with the FORTH detailed spectral radiation transfer model (RTM) using input data for various atmospheric and surface parameters, such as clouds, water vapor, ozone and surface albedo, taken from the NASA-Langley Global Earth Observing System (GEOS) database. The model spectral aerosol optical depth (AOD), single scattering albedo and asymmetry parameter are taken from the Global Aerosol Data Set and the NOAA Climate Data Record (CDR) version 2 of Advanced Very High resolution Radiometer (AVHRR) AOD dataset which is available over oceans at 0.63 microns and at 0.1˚ x0.1˚ . The aerosol DREs are computed at the surface, the top-of-atmosphere and within the atmosphere, over the period 1985-1995. Preliminary model results for the period 1990-1993 reveal a significant spatial and temporal variability of DREs over the EM Sea, for example larger values over the Aegean and Black Seas, surrounded by land areas with significant anthropogenic aerosol sources, and over the southernmost parts of EM Sea, affected by frequent Saharan dust export. The mean regional annual AODs range from 0.17±0.05 to 0.23±0.06. The corresponding regional annual DREs at surface range from -14±3 to -18±4 W/m2 (surface radiative cooling), while in the atmosphere they vary between 7±2 and 10±2 W/m2 (atmospheric heating), yielding a planetary cooling above the EM Sea between -6±1 and -8±2 W/m2. However, these AOD and DRE values vary depending on the criteria of data spatial and temporal availability applied in the AOD and DRE calculation, because of the limited availability of retrieved AVHRR AOD over specific areas and in specific days. The DREs reach larger magnitudes at pixel-level; for example the surface DREs slightly exceed -30 W/m2, whereas they take larger values (magnitudes larger than -50 W/m2 in summer) when computed on a monthly basis, and even larger values on daily basis. The model results underline the high spatial and temporal variability of aerosol DREs, and the care that must be taken when averaging over space and time. It also points to the need for availability of aerosol data with concurrent high spatial and temporal coverage and resolution, which should be sought in ongoing and future satellite missions.

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Processes governing phytoplankton blooms in estuaries. II: The role of horizontal transport

USGS Publications Warehouse

Lucas, L.V.; Koseff, Jeffrey R.; Monismith, Stephen G.; Cloern, J.E.; Thompson, J.K.

1999-01-01

The development and distribution of phytoplankton blooms in estuaries are functions of both local conditions (i.e. the production-loss balance for a water column at a particular spatial location) and large-scale horizontal transport. In this study, the second of a 2-paper series, we use a depth-averaged hydrodynamic-biological model to identify transport-related mechanisms impacting phytoplankton biomass accumulation and distribution on a system level. We chose South San Francisco Bay as a model domain, since its combination of a deep channel surrounded by broad shoals is typical of drowned-river estuaries. Five general mechanisms involving interaction of horizontal transport with variability in local conditions are discussed. Residual (on the order of days to weeks) transport mechanisms affecting bloom development and location include residence time/export, import, and the role of deep channel regions as conduits for mass transport. Interactions occurring on tidal time scales, i.e. on the order of hours) include the phasing of lateral oscillatory tidal flow relative to temporal changes in local net phytoplankton growth rates, as well as lateral sloshing of shoal-derived biomass into deep channel regions during ebb and back into shallow regions during flood tide. Based on these results, we conclude that: (1) while local conditions control whether a bloom is possible, the combination of transport and spatial-temporal variability in local conditions determines if and where a bloom will actually occur; (2) tidal-time-scale physical-biological interactions provide important mechanisms for bloom development and evolution. As a result of both subtidal and tidal-time-scale transport processes, peak biomass may not be observed where local conditions are most favorable to phytoplankton production, and inherently unproductive areas may be regions of high biomass accumulation.

Temporal trends in mercury concentrations in raptor flight feathers stored in an environmental specimen bank in Galicia (NW Spain) between 2000 and 2013.

PubMed

García-Seoane, Rita; Varela, Zulema; Carballeira, Alejo; Aboal, Jesús R; Fernández, J Ángel

2017-03-01

Temporal trends in Hg concentrations were investigated in primary flight feathers from 319 specimens of three birds of prey: P7 in the northern goshawk (Accipiter gentilis), P6 in the common buzzard (Buteo buteo) and P5 in the tawny owl (Strix aluco). The samples were stored in a regional environmental specimen bank and belonged to specimens which died between 2000 and 2013 in Galicia (NW Spain). We would expect to see a decline in Hg concentrations across the study period, as data of atmospheric emissions show a gradual reduction of this pollutant in Europe in the last two decades. The study did not reveal any temporal pattern in Hg concentrations of feathers in any of the three species for the study period, may be due to the persistence of Hg in the environment, but showed a low level of contamination by this metal in the study area. In addition, the results show high intra-specific, as well as, inter-annual and inter-specific variability in data, mainly attributed to the level of exposure of the raptors to this pollutant and to the biomagnification process of Hg through food chains. These findings indicate that the high variability can be a limiting factor in the use of raptors for biomonitoring temporal patterns of Hg, but nevertheless, the technique provides qualitative information about the amount of Hg that reach the top of the terrestrial food chains.

Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

NASA Astrophysics Data System (ADS)

Huang, X.; Tan, J.

2014-11-01

Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G ≡ (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

Variability and predictability of the streamflows in Coastal and Andean Ecuador

NASA Astrophysics Data System (ADS)

Quishpe-Vásquez, César; Córdoba-Machado, Samir; Palomino-Lemus, Reiner; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

The main objective of this study is to examine the variability and the predictability in available water resources in Coastal and Andean Ecuador. For this aim, we use the streamflow data from a network of hydrological stations, provided by the National Institute of Meteorology and Hydrology of Ecuador (IHNAMI), distributed over the Ecuadorian territory and strategically located in the watersheds of its main rivers. A number of 20 stations with a continuous period of daily data covering a period of 42 years (1973-2015) were selected. To analyze the spatio-temporal variability of streamflow in Ecuador, principal component analysis (PCA) along with a study of trends have been applied to the streamflow data at monthly time scales. The significance and magnitude of trends have been analyzed using Man-Kendall test and Sen slope. Moreover, to analyze the predictability of the streamflow, the spatio-temporal effects of the ENSO phenomenon on the country have been evaluated through a correlation analysis using different lags between different El Niño indices (Niño 1+2, Niño Modoki, Trans-Niño and Niño 3.4) and the seasonal streamflow. The results show two main regions that differ in terms of variability. We found that the variations in water resources have a close relationship between the magnitude and the seasonal distribution of the streamflow and the ENSO. However, each index shows a different impact on the streamflow depending on the season and the region. In general, the higher correlations between the ENSO indices and the streamflow are observed in the stations closer to the coast. KEY WORDS: Ecuador streamflow; trends; PCA; variability; predictability; ENSO. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Variability in avian eggshell colour: a comparative study of museum eggshells.

PubMed

Cassey, Phillip; Portugal, Steven J; Maurer, Golo; Ewen, John G; Boulton, Rebecca L; Hauber, Mark E; Blackburn, Tim M

2010-08-09

The exceptional diversity of coloration found in avian eggshells has long fascinated biologists and inspired a broad range of adaptive hypotheses to explain its evolution. Three main impediments to understanding the variability of eggshell appearance are: (1) the reliable quantification of the variation in eggshell colours; (2) its perception by birds themselves, and (3) its relation to avian phylogeny. Here we use an extensive museum collection to address these problems directly, and to test how diversity in eggshell coloration is distributed among different phylogenetic levels of the class Aves. Spectrophotometric data on eggshell coloration were collected from a taxonomically representative sample of 251 bird species to determine the change in reflectance across different wavelengths and the taxonomic level where the variation resides. As many hypotheses for the evolution of eggshell coloration assume that egg colours provide a communication signal for an avian receiver, we also modelled reflectance spectra of shell coloration for the avian visual system. We found that a majority of species have eggs with similar background colour (long wavelengths) but that striking differences are just as likely to occur between congeners as between members of different families. The region of greatest variability in eggshell colour among closely related species coincided with the medium-wavelength sensitive region around 500 nm. The majority of bird species share similar background eggshell colours, while the greatest variability among species aligns with differences along a red-brown to blue axis that most likely corresponds with variation in the presence and concentration of two tetrapyrrole pigments responsible for eggshell coloration. Additionally, our results confirm previous findings of temporal changes in museum collections, and this will be of particular concern for studies testing intraspecific hypotheses relating temporal patterns to adaptation of eggshell colour. We suggest that future studies investigating the phylogenetic association between the composition and concentration of eggshell pigments, and between the evolutionary drivers and functional impacts of eggshell colour variability will be most rewarding.

Developing priority variables ("ecosystem Essential Ocean Variables" - eEOVs) for observing dynamics and change in Southern Ocean ecosystems

NASA Astrophysics Data System (ADS)

Constable, Andrew J.; Costa, Daniel P.; Schofield, Oscar; Newman, Louise; Urban, Edward R.; Fulton, Elizabeth A.; Melbourne-Thomas, Jessica; Ballerini, Tosca; Boyd, Philip W.; Brandt, Angelika; de la Mare, Willaim K.; Edwards, Martin; Eléaume, Marc; Emmerson, Louise; Fennel, Katja; Fielding, Sophie; Griffiths, Huw; Gutt, Julian; Hindell, Mark A.; Hofmann, Eileen E.; Jennings, Simon; La, Hyoung Sul; McCurdy, Andrea; Mitchell, B. Greg; Moltmann, Tim; Muelbert, Monica; Murphy, Eugene; Press, Anthony J.; Raymond, Ben; Reid, Keith; Reiss, Christian; Rice, Jake; Salter, Ian; Smith, David C.; Song, Sun; Southwell, Colin; Swadling, Kerrie M.; Van de Putte, Anton; Willis, Zdenka

2016-09-01

Reliable statements about variability and change in marine ecosystems and their underlying causes are needed to report on their status and to guide management. Here we use the Framework on Ocean Observing (FOO) to begin developing ecosystem Essential Ocean Variables (eEOVs) for the Southern Ocean Observing System (SOOS). An eEOV is a defined biological or ecological quantity, which is derived from field observations, and which contributes significantly to assessments of Southern Ocean ecosystems. Here, assessments are concerned with estimating status and trends in ecosystem properties, attribution of trends to causes, and predicting future trajectories. eEOVs should be feasible to collect at appropriate spatial and temporal scales and are useful to the extent that they contribute to direct estimation of trends and/or attribution, and/or development of ecological (statistical or simulation) models to support assessments. In this paper we outline the rationale, including establishing a set of criteria, for selecting eEOVs for the SOOS and develop a list of candidate eEOVs for further evaluation. Other than habitat variables, nine types of eEOVs for Southern Ocean taxa are identified within three classes: state (magnitude, genetic/species, size spectrum), predator-prey (diet, foraging range), and autecology (phenology, reproductive rate, individual growth rate, detritus). Most candidates for the suite of Southern Ocean taxa relate to state or diet. Candidate autecological eEOVs have not been developed other than for marine mammals and birds. We consider some of the spatial and temporal issues that will influence the adoption and use of eEOVs in an observing system in the Southern Ocean, noting that existing operations and platforms potentially provide coverage of the four main sectors of the region - the East and West Pacific, Atlantic and Indian. Lastly, we discuss the importance of simulation modelling in helping with the design of the observing system in the long term. Regional boundary: south of 30°S.

Drivers of temporal beta diversity of a benthic community in a seasonally hypoxic fjord

PubMed Central

Curkan, Curtis; Tunnicliffe, Verena

2018-01-01

Global expansion of oxygen-deficient (hypoxic) waters will have detrimental effects on marine life in the Northeast Pacific Ocean (NEP) where some of the largest proportional losses in aerobic habitat are predicted to occur. However, few in situ studies have accounted for the high environmental variability in this region while including natural community-assembly dynamics. Here, we present results from a 14-month deployment of a benthic camera platform tethered to the VENUS cabled observatory in the seasonally hypoxic Saanich Inlet. Our time series continuously recorded natural cycles of deoxygenation and reoxygenation that allowed us to test whether a community from the NEP showed hysteresis in its recovery compared to hypoxia-induced decline, and to address the processes driving temporal beta diversity under variable states of hypoxia. Using high-frequency ecological time series, we reveal (i) differences in the response and recovery of the epibenthic community are rate-limited by recovery of the sessile species assemblage; (ii) both environmental and biological processes influence community assembly patterns at multiple timescales; and (iii) interspecific processes can drive temporal beta diversity in seasonal hypoxia. Ultimately, our results illustrate how different timescale-dependent drivers can influence the response and recovery of a marine habitat under increasing stress from environmental change. PMID:29765677

Frontal and temporal volumes in Childhood Absence Epilepsy.

PubMed

Caplan, Rochelle; Levitt, Jennifer; Siddarth, Prabha; Wu, Keng Nei; Gurbani, Suresh; Sankar, Raman; Shields, W Donald

2009-11-01

This study compared frontotemporal brain volumes in children with childhood absence epilepsy (CAE) to age- and gender-matched children without epilepsy. It also examined the association of these volumes with seizure, demographic, perinatal, intelligence quotient (IQ), and psychopathology variables. Twenty-six children with CAE, aged 7.5-11.8 years, and 37 children without epilepsy underwent brain magnetic resonance imaging (MRI) scans at 1.5 Tesla. Tissue was segmented, and total brain, frontal lobe, frontal parcellations, and temporal lobe volumes were computed. All children had IQ testing and structured psychiatric interviews. Parents provided seizure, perinatal, and behavioral information on each child. The CAE group had significantly smaller gray matter volumes of the left orbital frontal gyrus as well as both left and right temporal lobes compared to the age- and gender-matched children without epilepsy. In the CAE group these volumes were related to age, gender, ethnicity, and pregnancy complications but not to seizure, IQ, and psychopathology variables. In the group of children without epilepsy, however, the volumes were related to IQ. These findings suggest that CAE impacts brain development in regions implicated in behavior, cognition, and language. In addition to supporting the cortical focus theory of CAE, these findings also imply that CAE is not a benign disorder.

Drivers of temporal beta diversity of a benthic community in a seasonally hypoxic fjord

NASA Astrophysics Data System (ADS)

Chu, Jackson W. F.; Curkan, Curtis; Tunnicliffe, Verena

2018-04-01

Global expansion of oxygen-deficient (hypoxic) waters will have detrimental effects on marine life in the Northeast Pacific Ocean (NEP) where some of the largest proportional losses in aerobic habitat are predicted to occur. However, few in situ studies have accounted for the high environmental variability in this region while including natural community-assembly dynamics. Here, we present results from a 14-month deployment of a benthic camera platform tethered to the VENUS cabled observatory in the seasonally hypoxic Saanich Inlet. Our time series continuously recorded natural cycles of deoxygenation and reoxygenation that allowed us to test whether a community from the NEP showed hysteresis in its recovery compared to hypoxia-induced decline, and to address the processes driving temporal beta diversity under variable states of hypoxia. Using high-frequency ecological time series, we reveal (i) differences in the response and recovery of the epibenthic community are rate-limited by recovery of the sessile species assemblage; (ii) both environmental and biological processes influence community assembly patterns at multiple timescales; and (iii) interspecific processes can drive temporal beta diversity in seasonal hypoxia. Ultimately, our results illustrate how different timescale-dependent drivers can influence the response and recovery of a marine habitat under increasing stress from environmental change.

Incorporation of varying types of temporal data in a neural network

NASA Technical Reports Server (NTRS)

Cohen, M. E.; Hudson, D. L.

1992-01-01

Most neural network models do not specifically deal with temporal data. Handling of these variables is complicated by the different uses to which temporal data are put, depending on the application. Even within the same application, temporal variables are often used in a number of different ways. In this paper, types of temporal data are discussed, along with their implications for approximate reasoning. Methods for integrating approximate temporal reasoning into existing neural network structures are presented. These methods are illustrated in a medical application for diagnosis of graft-versus-host disease which requires the use of several types of temporal data.

Biases in Time-Averaged Field and Paleosecular Variation Studies

NASA Astrophysics Data System (ADS)

Johnson, C. L.; Constable, C.

2009-12-01

Challenges to constructing time-averaged field (TAF) and paleosecular variation (PSV) models of Earth’s magnetic field over million year time scales are the uneven geographical and temporal distribution of paleomagnetic data and the absence of full vector records of the magnetic field variability at any given site. Recent improvements in paleomagnetic data sets now allow regional assessment of the biases introduced by irregular temporal sampling and the absence of full vector information. We investigate these effects over the past few Myr for regions with large paleomagnetic data sets, where the TAF and/or PSV have been of previous interest (e.g., significant departures of the TAF from the field predicted by a geocentric axial dipole). We calculate the effects of excluding paleointensity data from TAF calculations, and find these to be small. For example, at Hawaii, we find that for the past 50 ka, estimates of the TAF direction are minimally affected if only paleodirectional data versus the full paleofield vector are used. We use resampling techniques to investigate biases incurred by the uneven temporal distribution. Key to the latter issue is temporal information on a site-by-site basis. At Hawaii, resampling of the paleodirectional data onto a uniform temporal distribution, assuming no error in the site ages, reduces the magnitude of the inclination anomaly for the Brunhes, Gauss and Matuyama epochs. However inclusion of age errors in the sampling procedure leads to TAF estimates that are close to those reported for the original data sets. We discuss the implications of our results for global field models.

Understanding the representativeness of FLUXNET for upscaling carbon flux from eddy covariance measurements

DOE PAGES

Kumar, Jitendra; Hoffman, Forrest M.; Hargrove, William W.; ...

2016-08-23

Eddy covariance data from regional flux networks are direct in situ measurement of carbon, water, and energy fluxes and are of vital importance for understanding the spatio-temporal dynamics of the the global carbon cycle. FLUXNET links regional networks of eddy covariance sites across the globe to quantify the spatial and temporal variability of fluxes at regional to global scales and to detect emergent ecosystem properties. This study presents an assessment of the representativeness of FLUXNET based on the recently released FLUXNET2015 data set. We present a detailed high resolution analysis of the evolving representativeness of FLUXNET through time. Results providemore » quantitative insights into the extent that various biomes are sampled by the network of networks, the role of the spatial distribution of the sites on the network scale representativeness at any given time, and how that representativeness has changed through time due to changing operational status and data availability at sites in the network. To realize the full potential of FLUXNET observations for understanding emergent ecosystem properties at regional and global scales, we present an approach for upscaling eddy covariance measurements. Informed by the representativeness of observations at the flux sites in the network, the upscaled data reflects the spatio-temporal dynamics of the carbon cycle captured by the in situ measurements. In conclusion, this study presents a method for optimal use of the rich point measurements from FLUXNET to derive an understanding of upscaled carbon fluxes, which can be routinely updated as new data become available, and direct network expansion by identifying regions poorly sampled by the current network.« less

The 5% difference: early sensory processing predicts sarcasm perception in schizophrenia and schizo-affective disorder.

PubMed

Kantrowitz, J T; Hoptman, M J; Leitman, D I; Silipo, G; Javitt, D C

2014-01-01

Intact sarcasm perception is a crucial component of social cognition and mentalizing (the ability to understand the mental state of oneself and others). In sarcasm, tone of voice is used to negate the literal meaning of an utterance. In particular, changes in pitch are used to distinguish between sincere and sarcastic utterances. Schizophrenia patients show well-replicated deficits in auditory function and functional connectivity (FC) within and between auditory cortical regions. In this study we investigated the contributions of auditory deficits to sarcasm perception in schizophrenia. Auditory measures including pitch processing, auditory emotion recognition (AER) and sarcasm detection were obtained from 76 patients with schizophrenia/schizo-affective disorder and 72 controls. Resting-state FC (rsFC) was obtained from a subsample and was analyzed using seeds placed in both auditory cortex and meta-analysis-defined core-mentalizing regions relative to auditory performance. Patients showed large effect-size deficits across auditory measures. Sarcasm deficits correlated significantly with general functioning and impaired pitch processing both across groups and within the patient group alone. Patients also showed reduced sensitivity to alterations in mean pitch and variability. For patients, sarcasm discrimination correlated exclusively with the level of rsFC within primary auditory regions whereas for controls, correlations were observed exclusively within core-mentalizing regions (the right posterior superior temporal gyrus, anterior superior temporal sulcus and insula, and left posterior medial temporal gyrus). These findings confirm the contribution of auditory deficits to theory of mind (ToM) impairments in schizophrenia, and demonstrate that FC within auditory, but not core-mentalizing, regions is rate limiting with respect to sarcasm detection in schizophrenia.

Intelligent Sampling of Hazardous Particle Populations in Resource-Constrained Environments

NASA Astrophysics Data System (ADS)

McCollough, J. P.; Quinn, J. M.; Starks, M. J.; Johnston, W. R.

2017-10-01

Sampling of anomaly-causing space environment drivers is necessary for both real-time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource-constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness.

Drought change in the middle reach of the Yellow River since the late Ming Dynasty and their correlation with runoff

NASA Astrophysics Data System (ADS)

Chen, F.

2017-12-01

Because of the reported decreasing trends in precipitation and streamflow in north-central China (Starting point of Ancient Silk Road), it is essential to understand long-term in water resource availability in this area. Thus, this research presents a new February-August PDSI reconstruction spanning CE 1615-2013 for the southern edge of the Gobi Desert under a highly variable arid and semi-arid climate in northern China. In addition to this new PDSI reconstruction, some previously published annual precipitation/PDSI reconstructions from the neighbouring regions were also used to infer the large-scale hydro-climatic signal of the middle reach of the Yellow River. Spatial correlation analyses with gridded precipitation data showed that the tree-ring records were indeed able to capture much of the regional interannual hydro-climatic signal variability. Using principal component analyses on the reconstructions and documentary records, many large-scale dry and flood events were found during the period AD 1615-2006. Many of these dry events have had profound impacts on the people of the study area over the past several centuries. Temporal correlations among the reconstruction and climatic indices, such as the El Niño-Southern Oscillation, demonstrate that water availability is influenced by tropical and high-latitude forcings in the Pacific rim. Continued work in this direction should enable us to understand better the hydrological change under global warming and the past climate variability of the silk road over long temporal and large spatial scales.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography

PubMed Central

Ozker, Muge; Schepers, Inga M.; Magnotti, John F.; Yoshor, Daniel; Beauchamp, Michael S.

2017-01-01

Human speech can be comprehended using only auditory information from the talker’s voice. However, comprehension is improved if the talker’s face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl’s gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech. PMID:28253074

Temporal variability of mass transport across Canary Islands Channels

NASA Astrophysics Data System (ADS)

Marrero-Díaz, Ángeles; Rodríguez-Santana, Ángel; José Machín, Francisco; García-Weil, Luis; Sangrà, Pablo; Vélez-Belchí, Pedro; Fraile-Nuez, Eugenio

2014-05-01

The equatorward flowing Canary Current (CC) is the main feature of the circulation in the Canary Islands region. The CC flow perturbation by the Canary Islands originate the Canary Eddy Corridor which is the major pathway for long lived eddies in the subtropical North Atlantic (Sangrà et al., 2009, DSR). Therefore the variability of the CC passing through the Canary Archipelago will have both local and regional importance. Past studies on the CC variability trough the Canary Islands point out a clearly seasonal variability (Fraile-Nuez et al, 2010 (JGR); Hernández-Guerra et al, 2002 (DSR)). However those studies where focused on the eastern islands channels missing the variability through the western island channels which are the main source of long lived eddies. In order to fill this gap from November 2012 until September 2013 we conducted trimonthly surveys crossing the whole islands channels using opportunity ships (Naviera Armas Ferries). XBT and XCTD where launched along the cross channels transects. Additionally a closed box circling the Archipelago was performed on October 2013 as part of the cruise RAPROCAN-2013 (IEO) using also XBT and XCTD. Dynamical variables where derived inferring salinity from S(T,p) analytical relationships for the region updated with new XCTD data. High resolution, vertical sections of temperature, potential density, geostrophic velocity and transport where obtained. Our preliminary results suggest that the CC suffer a noticeable acceleration in those islands channels where eddy shedding is more frequent. They also indicate a clearly seasonal variability of the flows passing the islands channels. With this regard we observed significant differences on the obtained seasonal variability with respect the cited past studies on the eastern islands channel (Lanzarote / Fuerteventura - Africa coast). This work was co-funded by Canary Government (TRAMIC project: PROID20100092) and the European Union (FEDER).

Ventricular enlargement in schizophrenia related to volume reduction of the thalamus, striatum, and superior temporal cortex.

PubMed

Gaser, Christian; Nenadic, Igor; Buchsbaum, Bradley R; Hazlett, Erin A; Buchsbaum, Monte S

2004-01-01

Enlargement of the lateral ventricles is among the most frequently reported macroscopic brain structural changes in schizophrenia, although variable in extent and localization. The authors investigated whether ventricular enlargement is related to regionally specific volume loss. High-resolution magnetic resonance imaging scans from 39 patients with schizophrenia were analyzed with deformation-based morphometry, a voxel-wise whole brain morphometric technique. Significant negative correlations with the ventricle-brain ratio were found for voxels in the left and right thalamus and posterior putamen and in the left superior temporal gyrus and insula. Thalamic shrinkage, especially of medial nuclei and the adjacent striatum and insular cortex, appear to be important contributors to ventricular enlargement in schizophrenia.

Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity.

PubMed

Karmakar, Chandan K; Khandoker, Ahsan H; Voss, Andreas; Palaniswami, Marimuthu

2011-03-03

A novel descriptor (Complex Correlation Measure (CCM)) for measuring the variability in the temporal structure of Poincaré plot has been developed to characterize or distinguish between Poincaré plots with similar shapes. This study was designed to assess the changes in temporal structure of the Poincaré plot using CCM during atropine infusion, 70° head-up tilt and scopolamine administration in healthy human subjects. CCM quantifies the point-to-point variation of the signal rather than gross description of the Poincaré plot. The physiological relevance of CCM was demonstrated by comparing the changes in CCM values with autonomic perturbation during all phases of the experiment. The sensitivities of short term variability (SD1), long term variability (SD2) and variability in temporal structure (CCM) were analyzed by changing the temporal structure by shuffling the sequences of points of the Poincaré plot. Surrogate analysis was used to show CCM as a measure of changes in temporal structure rather than random noise and sensitivity of CCM with changes in parasympathetic activity. CCM was found to be most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2. The values of all descriptors decreased with decrease in parasympathetic activity during atropine infusion and 70° head-up tilt phase. In contrast, values of all descriptors increased with increase in parasympathetic activity during scopolamine administration. The concordant reduction and enhancement in CCM values with parasympathetic activity indicates that the temporal variability of Poincaré plot is modulated by the parasympathetic activity which correlates with changes in CCM values. CCM is more sensitive than SD1 and SD2 to changes of parasympathetic activity.

Spatial and temporal stability of temperature in the first-level basins of China during 1951-2013

NASA Astrophysics Data System (ADS)

Cheng, Yuting; Li, Peng; Xu, Guoce; Li, Zhanbin; Cheng, Shengdong; Wang, Bin; Zhao, Binhua

2018-05-01

In recent years, global warming has attracted great attention around the world. Temperature change is not only involved in global climate change but also closely linked to economic development, the ecological environment, and agricultural production. In this study, based on temperature data recorded by 756 meteorological stations in China during 1951-2013, the spatial and temporal stability characteristics of annual temperature in China and its first-level basins were investigated using the rank correlation coefficient method, the relative difference method, rescaled range (R/S) analysis, and wavelet transforms. The results showed that during 1951-2013, the spatial variation of annual temperature belonged to moderate variability in the national level. Among the first-level basins, the largest variation coefficient was 114% in the Songhuajiang basin and the smallest variation coefficient was 10% in the Huaihe basin. During 1951-2013, the spatial distribution pattern of annual temperature presented extremely strong spatial and temporal stability characteristics in the national level. The variation range of Spearman's rank correlation coefficient was 0.97-0.99, and the spatial distribution pattern of annual temperature showed an increasing trend. In the national level, the Liaohe basin, the rivers in the southwestern region, the Haihe basin, the Yellow River basin, the Yangtze River basin, the Huaihe basin, the rivers in the southeastern region, and the Pearl River basin all had representative meteorological stations for annual temperature. In the Songhuajiang basin and the rivers in the northwestern region, there was no representative meteorological station. R/S analysis, the Mann-Kendall test, and the Morlet wavelet analysis of annual temperature showed that the best representative meteorological station could reflect the variation trend and the main periodic changes of annual temperature in the region. Therefore, strong temporal stability characteristics exist for annual temperature in China and its first-level basins. It was therefore feasible to estimate the annual average temperature by the annual temperature recorded by the representative meteorological station in the region. Moreover, it was of great significance to assess average temperature changes quickly and forecast future change tendencies in the region.

Late Holocene sea level variability and Atlantic Meridional Overturning Circulation

USGS Publications Warehouse

Cronin, Thomas M.; Farmer, Jesse R.; Marzen, R. E.; Thomas, E.; Varekamp, J.C.

2014-01-01

Pre-twentieth century sea level (SL) variability remains poorly understood due to limits of tide gauge records, low temporal resolution of tidal marsh records, and regional anomalies caused by dynamic ocean processes, notably multidecadal changes in Atlantic Meridional Overturning Circulation (AMOC). We examined SL and AMOC variability along the eastern United States over the last 2000 years, using a SL curve constructed from proxy sea surface temperature (SST) records from Chesapeake Bay, and twentieth century SL-sea surface temperature (SST) relations derived from tide gauges and instrumental SST. The SL curve shows multidecadal-scale variability (20–30 years) during the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA), as well as the twentieth century. During these SL oscillations, short-term rates ranged from 2 to 4 mm yr−1, roughly similar to those of the last few decades. These oscillations likely represent internal modes of climate variability related to AMOC variability and originating at high latitudes, although the exact mechanisms remain unclear. Results imply that dynamic ocean changes, in addition to thermosteric, glacio-eustatic, or glacio-isostatic processes are an inherent part of SL variability in coastal regions, even during millennial-scale climate oscillations such as the MCA and LIA and should be factored into efforts that use tide gauges and tidal marsh sediments to understand global sea level rise.

Human cranial anatomy and the differential preservation of population history and climate signatures.

PubMed

Harvati, Katerina; Weaver, Timothy D

2006-12-01

Cranial morphology is widely used to reconstruct evolutionary relationships, but its reliability in reflecting phylogeny and population history has been questioned. Some cranial regions, particularly the face and neurocranium, are believed to be influenced by the environment and prone to convergence. Others, such as the temporal bone, are thought to reflect more accurately phylogenetic relationships. Direct testing of these hypotheses was not possible until the advent of large genetic data sets. The few relevant studies in human populations have had intriguing but possibly conflicting results, probably partly due to methodological differences and to the small numbers of populations used. Here we use three-dimensional (3D) geometric morphometrics methods to test explicitly the ability of cranial shape, size, and relative position/orientation of cranial regions to track population history and climate. Morphological distances among 13 recent human populations were calculated from four 3D landmark data sets, respectively reflecting facial, neurocranial, and temporal bone shape; shape and relative position; overall cranial shape; and centroid sizes. These distances were compared to neutral genetic and climatic distances among the same, or closely matched, populations. Results indicate that neurocranial and temporal bone shape track neutral genetic distances, while facial shape reflects climate; centroid size shows a weak association with climatic variables; and relative position/orientation of cranial regions does not appear correlated with any of these factors. Because different cranial regions preserve population history and climate signatures differentially, caution is suggested when using cranial anatomy for phylogenetic reconstruction. Copyright (c) 2006 Wiley-Liss, Inc.

Patterns in Temporal Variability of Temperature, Oxygen and pH along an Environmental Gradient in a Coral Reef

PubMed Central

Guadayol, Òscar; Silbiger, Nyssa J.; Donahue, Megan J.; Thomas, Florence I. M.

2014-01-01

Spatial and temporal environmental variability are important drivers of ecological processes at all scales. As new tools allow the in situ exploration of individual responses to fluctuations, ecologically meaningful ways of characterizing environmental variability at organism scales are needed. We investigated the fine-scale spatial heterogeneity of high-frequency temporal variability in temperature, dissolved oxygen concentration, and pH experienced by benthic organisms in a shallow coastal coral reef. We used a spatio-temporal sampling design, consisting of 21 short-term time-series located along a reef flat-to-reef slope transect, coupled to a long-term station monitoring water column changes. Spectral analyses revealed sharp gradients in variance decomposed by frequency, as well as differences between physically-driven and biologically-reactive parameters. These results highlight the importance of environmental variance at organismal scales and present a new sampling scheme for exploring this variability in situ. PMID:24416364

Medium-range, objective predictions of thunderstorm location and severity for aviation

NASA Technical Reports Server (NTRS)

Wilson, G. S.; Turner, R. E.

1981-01-01

This paper presents a computerized technique for medium-range (12-48h) prediction of both the location and severity of thunderstorms utilizing atmospheric predictions from the National Meteorological Center's limited-area fine-mesh model (LFM). A regional-scale analysis scheme is first used to examine the spatial and temporal distributions of forecasted variables associated with the structure and dynamics of mesoscale systems over an area of approximately 10 to the 6th sq km. The final prediction of thunderstorm location and severity is based upon an objective combination of these regionally analyzed variables. Medium-range thunderstorm predictions are presented for the late afternoon period of April 10, 1979, the day of the Wichita Falls, Texas tornado. Conventional medium-range thunderstorm forecasts, made from observed data, are presented with the case study to demonstrate the possible application of this objective technique in improving 12-48 h thunderstorm forecasts for aviation.

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

NASA Astrophysics Data System (ADS)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were performed in the PMIP3 project. The proxy data syntheses consist either of raw pollen data or of normally distributed climate data from preprocessed proxy records. Future extensions of our method contain the inclusion of other proxy types (transfer functions), the implementation of other spatial interpolation techniques, the use of age uncertainties, and the extension to spatio-temporal reconstructions of the last deglaciation. Our work is part of the PalMod project funded by the German Federal Ministry of Education and Science (BMBF).

Current and Future Decadal Trends in the Oceanic Carbon Uptake Are Dominated by Internal Variability

NASA Astrophysics Data System (ADS)

Li, Hongmei; Ilyina, Tatiana

2018-01-01

We investigate the internal decadal variability of the ocean carbon uptake using 100 ensemble simulations based on the Max Planck Institute Earth system model (MPI-ESM). We find that on decadal time scales, internal variability (ensemble spread) is as large as the forced temporal variability (ensemble mean), and the largest internal variability is found in major carbon sink regions, that is, the 50-65°S band of the Southern Ocean, the North Pacific, and the North Atlantic. The MPI-ESM ensemble produces both positive and negative 10 year trends in the ocean carbon uptake in agreement with observational estimates. Negative decadal trends are projected to occur in the future under RCP4.5 scenario. Due to the large internal variability, the Southern Ocean and the North Pacific require the most ensemble members (more than 53 and 46, respectively) to reproduce the forced decadal trends. This number increases up to 79 in future decades as CO2 emission trajectory changes.