Exploring the Links in Monthly to Decadal Variability of the Atmospheric Water Balance Over the Wettest Regions in ERA-20C

NASA Astrophysics Data System (ADS)

Nogueira, M.

2017-10-01

Monthly-to-decadal variability of the regional precipitation over Intertropical Convergence Zone and north-Atlantic and north-Pacific storm tracks was investigated using ERA-20C reanalysis. Satellite-based precipitation (P) and evaporation (E) climatological patterns were well reproduced by ERA-20C. Regional P and E monthly time series displayed 20% differences, but these decreased rapidly with time scale ( 10% at yearly time scales). Spectral analysis showed good scale-by-scale statistical agreement between ERA-20C and observations. Using ERA-Interim showed no improvement despite the much wider range of information assimilated (including satellites). Remarkably high Detrended Cross-Correlation Analysis coefficients (ρDCCA > 0.7 and often ρDCCA > 0.9) revealed tight links between the nonperiodic variability of P, moisture divergence (DIV), and pressure velocity (ω) at monthly-to-decadal time scales over all the wet regions. In contrast, ρDCCA was essentially nonsignificant between nonperiodic P and E or sea surface temperature (SST). Thus, the nonperiodic monthly-to-decadal variability of precipitation in these regions is almost fully controlled by dynamics and not by local E or SST (suggested by Clausius-Clapeyron relation). Analysis of regional nonperiodic standard deviations and power spectra (and respective spectral exponents, β) provided further robustness to this conclusion. Finally, clear transitions in β for P, DIV, and ω between tropical and storm track regions were found. The latter is dominated by transient storms, with energy accumulation at synoptic scales and β < 0.1 at monthly-to-decadal time scales, implying that variability and information creation decrease rapidly with time scale. Larger β values (0.2 to 0.4) were found in the tropics, implying longer-range autocorrelations and slower decreasing variability and information creation with time scale, consistent with the important forcing from internal modes of variability (e.g., El Niño-Southern Oscillation).

The sensitivity of the atmospheric branch of the global water cycle to temperature fluctuations at synoptic to decadal time-scales in different satellite- and model-based products

NASA Astrophysics Data System (ADS)

Nogueira, Miguel

2018-02-01

Spectral analysis of global-mean precipitation, P, evaporation, E, precipitable water, W, and surface temperature, Ts, revealed significant variability from sub-daily to multi-decadal time-scales, superposed on high-amplitude diurnal and yearly peaks. Two distinct regimes emerged from a transition in the spectral exponents, β. The weather regime covering time-scales < 10 days with β ≥ 1; and the macroweather regime extending from a few months to a few decades with 0 <β <1. Additionally, the spectra showed a generally good statistical agreement amongst several different model- and satellite-based datasets. Detrended cross-correlation analysis (DCCA) revealed three important results which are robust across all datasets: (1) Clausius-Clapeyron (C-C) relationship is the dominant mechanism of W non-periodic variability at multi-year time-scales; (2) C-C is not the dominant control of W, P or E non-periodic variability at time-scales below about 6 months, where the weather regime is approached and other mechanisms become important; (3) C-C is not a dominant control for P or E over land throughout the entire time-scale range considered. Furthermore, it is suggested that the atmosphere and oceans start to act as a single coupled system at time-scales > 1-2 years, while at time-scales < 6 months they are not the dominant drivers of each other. For global-ocean and full-globe averages, ρDCCA showed large spread of the C-C importance for P and E variability amongst different datasets at multi-year time-scales, ranging from negligible (< 0.3) to high ( 0.6-0.8) values. Hence, state-of-the-art climate datasets have significant uncertainties in the representation of macroweather precipitation and evaporation variability and its governing mechanisms.

Characteristic variations of sea surface temperature with multiple time scales in the North Pacific

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

Tanimoto, Youichi; Hanawa, Kimio; Toba, Yoshiaki

1993-06-01

It is unclear whether the recent increases in global temperatures are really due to the increase of greenhouse gases or are a manifestation of natural variability. Temporal evolution and spectral structure of sea surface temperature (SST) anomalies in the North Pacific over the last 37 years are investigated on the three characteristic time scales: shorter than 24 months (HF), 24-60 months (ES), and longer than 60 months (DC). The leading empirical-orthogonal function (EOF) for the DC time scale is characterized by a zonally elongated monopole centered at around 40[degrees]N, 180[degrees]. The leading EOF for the HF time scale is somewhatmore » similar to that for the DC time scale, although there are two centers of action with the same polarity at the mid and western Pacific. The leading EOF for the ES time scale, however, exhibits a different pattern whose center of action at the mid Pacific is located farther southeastward. In the time evolution of the SST anomalies associated with the leading EOF of the DC time scale, several anomaly periods can be identified that last five years or longer. The transition from a persistent period to another with the opposite polarity is generally very brief, except for the one that lasts throughout the late 1960s. The EOF analysis was repeated separately on these persistent anomaly periods and the long transition period. The spatial structure of the leading EOF of the SST variability with the ES time scale is found to be sensitive to the polarity of the decadal anomaly. These results are suggestive of the possible influence of the decadal SST variability upon the spatial structure of the variability with shorter time scales. 31 refs., 8 figs.« less

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.

Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China.

PubMed

Liu, Huiyu; Zhang, Mingyang; Lin, Zhenshan

2017-10-05

Climate changes are considered to significantly impact net primary productivity (NPP). However, there are few studies on how climate changes at multiple time scales impact NPP. With MODIS NPP product and station-based observations of sunshine duration, annual average temperature and annual precipitation, impacts of climate changes at different time scales on annual NPP, have been studied with EEMD (ensemble empirical mode decomposition) method in the Karst area of northwest Guangxi, China, during 2000-2013. Moreover, with partial least squares regression (PLSR) model, the relative importance of climatic variables for annual NPP has been explored. The results show that (1) only at quasi 3-year time scale do sunshine duration and temperature have significantly positive relations with NPP. (2) Annual precipitation has no significant relation to NPP by direct comparison, but significantly positive relation at 5-year time scale, which is because 5-year time scale is not the dominant scale of precipitation; (3) the changes of NPP may be dominated by inter-annual variabilities. (4) Multiple time scales analysis will greatly improve the performance of PLSR model for estimating NPP. The variable importance in projection (VIP) scores of sunshine duration and temperature at quasi 3-year time scale, and precipitation at quasi 5-year time scale are greater than 0.8, indicating important for NPP during 2000-2013. However, sunshine duration and temperature at quasi 3-year time scale are much more important. Our results underscore the importance of multiple time scales analysis for revealing the relations of NPP to changing climate.

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

On the use of variability time-scales as an early classifier of radio transients and variables

NASA Astrophysics Data System (ADS)

Pietka, M.; Staley, T. D.; Pretorius, M. L.; Fender, R. P.

2017-11-01

We have shown previously that a broad correlation between the peak radio luminosity and the variability time-scales, approximately L ∝ τ5, exists for variable synchrotron emitting sources and that different classes of astrophysical sources occupy different regions of luminosity and time-scale space. Based on those results, we investigate whether the most basic information available for a newly discovered radio variable or transient - their rise and/or decline rate - can be used to set initial constraints on the class of events from which they originate. We have analysed a sample of ≈800 synchrotron flares, selected from light curves of ≈90 sources observed at 5-8 GHz, representing a wide range of astrophysical phenomena, from flare stars to supermassive black holes. Selection of outbursts from the noisy radio light curves has been done automatically in order to ensure reproducibility of results. The distribution of rise/decline rates for the selected flares is modelled as a Gaussian probability distribution for each class of object, and further convolved with estimated areal density of that class in order to correct for the strong bias in our sample. We show in this way that comparing the measured variability time-scale of a radio transient/variable of unknown origin can provide an early, albeit approximate, classification of the object, and could form part of a suite of measurements used to provide early categorization of such events. Finally, we also discuss the effect scintillating sources will have on our ability to classify events based on their variability time-scales.

Long-term variability of T Tauri stars using WASP

NASA Astrophysics Data System (ADS)

Rigon, Laura; Scholz, Alexander; Anderson, David; West, Richard

2017-03-01

We present a reference study of the long-term optical variability of young stars using data from the WASP project. Our primary sample is a group of well-studied classical T Tauri stars (CTTSs), mostly in Taurus-Auriga. WASP light curves cover time-scales of up to 7 yr and typically contain 10 000-30 000 data points. We quantify the variability as a function of time-scale using the time-dependent standard deviation 'pooled sigma'. We find that the overwhelming majority of CTTSs have a low-level variability with σ < 0.3 mag dominated by time-scales of a few weeks, consistent with rotational modulation. Thus, for most young stars, monitoring over a month is sufficient to constrain the total amount of variability over time-scales of up to a decade. The fraction of stars with a strong optical variability (σ > 0.3 mag) is 21 per cent in our sample and 21 per cent in an unbiased control sample. An even smaller fraction (13 per cent in our sample, 6 per cent in the control) show evidence for an increase in variability amplitude as a function of time-scale from weeks to months or years. The presence of long-term variability correlates with the spectral slope at 3-5 μm, which is an indicator of inner disc geometry, and with the U-B band slope, which is an accretion diagnostics. This shows that the long-term variations in CTTSs are predominantly driven by processes in the inner disc and in the accretion zone. Four of the stars with long-term variations show periods of 20-60 d, significantly longer than the rotation periods and stable over months to years. One possible explanation is cyclic changes in the interaction between the disc and the stellar magnetic field.

Time-variant Lagrangian transport formulation reduces aggregation bias of water and solute mean travel time in heterogeneous catchments

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Botter, Gianluca; Foufoula-Georgiou, Efi

2017-05-01

Lack of hydro-bio-chemical data at subcatchment scales necessitates adopting an aggregated system approach for estimating water and solute transport properties, such as residence and travel time distributions, at the catchment scale. In this work, we show that within-catchment spatial heterogeneity, as expressed in spatially variable discharge-storage relationships, can be appropriately encapsulated within a lumped time-varying stochastic Lagrangian formulation of transport. This time (variability) for space (heterogeneity) substitution yields mean travel times (MTTs) that are not significantly biased to the aggregation of spatial heterogeneity. Despite the significant variability of MTT at small spatial scales, there exists a characteristic scale above which the MTT is not impacted by the aggregation of spatial heterogeneity. Extensive simulations of randomly generated river networks reveal that the ratio between the characteristic scale and the mean incremental area is on average independent of river network topology and the spatial arrangement of incremental areas.

Time Scales and Sources of European Temperature Variability

NASA Astrophysics Data System (ADS)

Årthun, Marius; Kolstad, Erik W.; Eldevik, Tor; Keenlyside, Noel S.

2018-04-01

Skillful predictions of continental climate would be of great practical benefit for society and stakeholders. It nevertheless remains fundamentally unresolved to what extent climate is predictable, for what features, at what time scales, and by which mechanisms. Here we identify the dominant time scales and sources of European surface air temperature (SAT) variability during the cold season using a coupled climate reanalysis, and a statistical method that estimates SAT variability due to atmospheric circulation anomalies. We find that eastern Europe is dominated by subdecadal SAT variability associated with the North Atlantic Oscillation, whereas interdecadal and multidecadal SAT variability over northern and southern Europe are thermodynamically driven by ocean temperature anomalies. Our results provide evidence that temperature anomalies in the North Atlantic Ocean are advected over land by the mean westerly winds and, hence, provide a mechanism through which ocean temperature controls the variability and provides predictability of European SAT.

Extracting information from AGN variability

NASA Astrophysics Data System (ADS)

Kasliwal, Vishal P.; Vogeley, Michael S.; Richards, Gordon T.

2017-09-01

Active galactic nuclei (AGNs) exhibit rapid, high-amplitude stochastic flux variations across the entire electromagnetic spectrum on time-scales ranging from hours to years. The cause of this variability is poorly understood. We present a Green's function-based method for using variability to (1) measure the time-scales on which flux perturbations evolve and (2) characterize the driving flux perturbations. We model the observed light curve of an AGN as a linear differential equation driven by stochastic impulses. We analyse the light curve of the Kepler AGN Zw 229-15 and find that the observed variability behaviour can be modelled as a damped harmonic oscillator perturbed by a coloured noise process. The model power spectrum turns over on time-scale 385 d. On shorter time-scales, the log-power-spectrum slope varies between 2 and 4, explaining the behaviour noted by previous studies. We recover and identify both the 5.6 and 67 d time-scales reported by previous work using the Green's function of the Continuous-time AutoRegressive Moving Average equation rather than by directly fitting the power spectrum of the light curve. These are the time-scales on which flux perturbations grow, and on which flux perturbations decay back to the steady-state flux level, respectively. We make the software package kālī used to study light curves using our method available to the community.

Long time scale hard X-ray variability in Seyfert 1 galaxies

NASA Astrophysics Data System (ADS)

Markowitz, Alex Gary

This dissertation examines the relationship between long-term X-ray variability characteristics, black hole mass, and luminosity of Seyfert 1 Active Galactic Nuclei. High dynamic range power spectral density functions (PSDs) have been constructed for six Seyfert 1 galaxies. These PSDs show "breaks" or characteristic time scales, typically on the order of a few days. There is resemblance to PSDs of lower-mass Galactic X-ray binaries (XRBs), with the ratios of putative black hole masses and variability time scales approximately the same (106--7) between the two classes of objects. The data are consistent with a linear correlation between Seyfert PSD break time scale and black hole mass estimate; the relation extrapolates reasonably well over 6--7 orders of magnitude to XRBs. All of this strengthens the case for a physical similarity between Seyfert galaxies and XRBs. The first six years of RXTE monitoring of Seyfert 1s have been systematically analyzed to probe hard X-ray variability on multiple time scales in a total of 19 Seyfert is in an expansion of the survey of Markowitz & Edelson (2001). Correlations between variability amplitude, luminosity, and black hole mass are explored, the data support the model of PSD movement with black hole mass suggested by the PSD survey. All of the continuum variability results are consistent with relatively more massive black holes hosting larger X-ray emission regions, resulting in 'slower' observed variability. Nearly all sources in the sample exhibit stronger variability towards softer energies, consistent with softening as they brighten. Direct time-resolved spectral fitting has been performed on continuous RXTE monitoring of seven Seyfert is to study long-term spectral variability and Fe Kalpha variability characteristics. The Fe Kalpha line displays a wide range of behavior but varies less strongly than the broadband continuum. Overall, however, there is no strong evidence for correlated variability between the line and continuum, severely challenging models in which the line tracks continuum variations modified only by a light-travel time delay. This experiment yields further support for spectral softening as continuum flux increases.

Variability and prediction of freshwater and nitrate fluxes for the Louisiana-Texas shelf: Mississippi and Atchafalaya River source functions

USGS Publications Warehouse

Bratkovich, A.; Dinnel, S.P.; Goolsby, D.A.

1994-01-01

Time histories of riverine water discharge, nitrate concentration, and nitrate, flux have been analyzed for the Mississippi and Atchafalaya rivers. Results indicate that water discharge variability is dominated by the annual cycle and shorter-time-scale episodic events presumably associated with snowmelt runoff and spring or summer rains. Interannual variability in water discharge is relatively small compared to the above. In contrast, nitrate concentration exhibits strongest variability at decadal time scales. The interannual variability is not monotonic but more complicated in structure. Weak covariability between water discharge and nitrate concentration leads to a relatively “noisy” nitrate flux signal. Nitrate flux variations exhibit a low-amplitude, long-term modulation of a dominant annual cycle. Predictor-hindcastor analyses indicate that skilled forecasts of nitrate concentration and nitrate flux fields are feasible. Water discharge was the most reliably hindcast (on seasonal to interannual time scales) due to the fundamental strength of the annual hydrologic cycle. However, the forecasting effort for this variable was less successful than the hindcasting effort, mostly due to a phase shift in the annual cycle during our relatively short test period (18 mo). Nitrate concentration was more skillfully predicted (seasonal to interannual time scales) due to the relative dominance of the decadal-scale portion of the signal. Nitrate flux was also skillfully forecast even though historical analyses seemed to indicate that it should be more difficult to predict than either water discharge or nitrate concentration.

Learning Across Time Scales: Science, Policy, Management, and Communication

NASA Astrophysics Data System (ADS)

Stewart, M. M.

2002-05-01

This presentation will draw together common themes raised in the session and discuss lessons learned across time scales and their implications for managers and policy makers concerned with both climate change and variability. Session themes will be examined in the context of the upcoming World Summit on Sustainable Development (WSSD) and considered as opportunities for linking climate change policy discussions with lessons learned from the study of adaptation on seasonal to interannual time scales. The presentation will raise questions about future research directions, discuss recommendations for promoting learning across time scales, and explore options for better communicating the links between climate change and variability.

Characterization of the infrared/X-ray subsecond variability for the black hole transient GX 339-4

NASA Astrophysics Data System (ADS)

Vincentelli, F. M.; Casella, P.; Maccarone, T. J.; Uttley, P.; Gandhi, P.; Belloni, T.; De Marco, B.; Russell, D. M.; Stella, L.; O'Brien, K.

2018-07-01

We present a detailed analysis of the X-ray/IR fast variability of the Black-Hole Transient GX 339-4 during its low/hard state in 2008 August. Thanks to simultaneous high time resolution observations made with the VLT and RXTE, we performed the first characterization of the subsecond variability in the near-infrared band - and of its correlation with the X-rays - for a low-mass X-ray binary, using both time- and frequency-domain techniques. We found a power-law correlation between the X-ray and infrared fluxes when measured on time-scales of 16 s, with a marginally variable slope, steeper than the one found on time-scales of days at similar flux levels. We suggest the variable slope - if confirmed - could be due to the infrared flux being a non-constant combination of both optically thin and optically thick synchrotron emission from the jet, as a result of a variable self-absorption break. From cross spectral analysis, we found an approximately constant infrared time lag of ≈0.1 s, and a very high coherence of ˜90 per cent on time-scales of tens of seconds, slowly decreasing towards higher frequencies. Finally, we report on the first detection of a linear rms-flux relation in the emission from a low-mass X-ray binary jet, on time-scales where little correlation is found between the X-rays and the jet emission itself. This suggests that either the inflow variations and jet IR emission are coupled by a non-linear or time-variable transform, or that the IR rms-flux relation is not transferred from the inflow to the jet, but is an intrinsic property of emission processes in the jet.

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.

Characterizing the Influence of the General Circulation on Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Rozendaal, Margaret A.; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

The seasonal and intraseasonal variability of boundary layer cloud in the subtropical eastern oceans are studied using combined data from the International Satellite Cloud Climatology Project (ISCCP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. Spectral analysis reveals that most of the time variability of cloud properties occurs on seasonal to annual time scales. The variance decreases one to two orders of magnitude for each decade of time scale decrease, indicating that daily to monthly time scales have smaller, but non-negligible variability. The length of these dominant time scales suggests that the majority of the variability is influenced by the general circulation and its interaction with boundary layer turbulence, rather than a product of boundary layer turbulence alone. Previous datasets have lacked the necessary resolution in either time or in space to properly characterize variability on synoptic scales; this is remedied by using global satellite-retrieved cloud properties. We characterize the intraseasonal subtropical cloud variability in both hemispheres and in different seasons. In addition to cloud fraction, we examine variability of cloud optical thickness - cloud top pressure frequency distributions. Despite the large concentration of research on the variability of Northern Hemisphere (NH) regions during summer, it is noted that the largest amplitude intraseasonal variability in the NH regions occurs during local winter. The effect of intraseasonal variability on the calculation and interpretation of seasonal results is investigated. Decreases in seasonally averaged cloud cover, optical thickness and cloud top pressure from the May-through-September season to the November-through-March season are most apparent in the NH regions. Further analysis indicates that these changes are due to an increase in frequency, but a decrease in the persistence of synoptic events. In addition, changes in cloud top pressure and optical thickness characteristics from the summer to winter seasons indicate that the NH subtropics undergo a change in dynamic regime with season. This change appears in the cloud fields as a shift from the more commonly seen lower-altitude, thicker optical thickness clouds to higher-altitude, thinner clouds. The latter cloud-type is associated with the lower sea level pressure, upward vertical velocity phase of the synoptic wave. Intraseasonal changes in cloud properties in the Southern Hemisphere and NH summer are much smaller in amplitude. Although they also appear to be linked to changes in the large-scale dynamics, similarly to NH winter variations, the relationships are more ambiguous due to the small amplitudes and longer time scales. We attempt to interpret some of these relationships using the results of the Betts and Ridgway (1989) box model. However, these results cannot consistently explain the patterns when results from all regions are considered, implying that this model may not adequately explain all the processes involved in the variability.

The Causal Connection Between Disc and Power-Law Variability in Hard State Black Hole X-Ray Binaries

NASA Technical Reports Server (NTRS)

Uttley, P.; Wilkinson, T.; Cassatella, P.; Wilms, J.; Pottschimdt, K.; Hanke, M.; Boeck, M.

2010-01-01

We use the XMM-Newton EPIC-pn instrument in timing mode to extend spectral time-lag studies of hard state black hole X-ray binaries into the soft X-ray band. \\Ve show that variations of the disc blackbody emission substantially lead variations in the power-law emission, by tenths of a second on variability time-scales of seconds or longer. The large lags cannot be explained by Compton scattering but are consistent with time-delays due to viscous propagation of mass accretion fluctuations in the disc. However, on time-scales less than a second the disc lags the power-law variations by a few ms, consistent with the disc variations being dominated by X-ray heating by the power-law, with the short lag corresponding to the light-travel time between the power-law emitting region and the disc. Our results indicate that instabilities in the accretion disc are responsible for continuum variability on time-scales of seconds or longer and probably also on shorter time-scales.

Evaluating the effect of internal aperture variability on transport in kilometer scale discrete fracture networks

DOE PAGES

Makedonska, Nataliia; Hyman, Jeffrey D.; Karra, Satish; ...

2016-08-01

The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale fracture networks has been under debate for a long time, since the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We addressmore » this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P 32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. The recently developed discrete fracture network (DFN) simulation capability, dfnWorks, is used to generate kilometer scale DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time, , and cumulative retention, , are calculated along particles streamlines. As a result, it is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture aperture variability than the tails of travel time distributions, where no significant effect of the in-fracture aperture variations and spatial correlation length is observed.« less

Evaluating the effect of internal aperture variability on transport in kilometer scale discrete fracture networks

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

Makedonska, Nataliia; Hyman, Jeffrey D.; Karra, Satish

The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale fracture networks has been under debate for a long time, since the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We addressmore » this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P 32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. The recently developed discrete fracture network (DFN) simulation capability, dfnWorks, is used to generate kilometer scale DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time, , and cumulative retention, , are calculated along particles streamlines. As a result, it is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture aperture variability than the tails of travel time distributions, where no significant effect of the in-fracture aperture variations and spatial correlation length is observed.« less

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds.

PubMed

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie; Huang, Xianfei

2018-04-13

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km², 4.50 km², and 1.87 km², respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content.

A Systematic Search for Short-term Variability of EGRET Sources

NASA Technical Reports Server (NTRS)

Wallace, P. M.; Griffis, N. J.; Bertsch, D. L.; Hartman, R. C.; Thompson, D. J.; Kniffen, D. A.; Bloom, S. D.

2000-01-01

The 3rd EGRET Catalog of High-energy Gamma-ray Sources contains 170 unidentified sources, and there is great interest in the nature of these sources. One means of determining source class is the study of flux variability on time scales of days; pulsars are believed to be stable on these time scales while blazers are known to be highly variable. In addition, previous work has demonstrated that 3EG J0241-6103 and 3EG J1837-0606 are candidates for a new gamma-ray source class. These sources near the Galactic plane display transient behavior but cannot be associated with any known blazers. Although, many instances of flaring AGN have been reported, the EGRET database has not been systematically searched for occurrences of short-timescale (approximately 1 day) variability. These considerations have led us to conduct a systematic search for short-term variability in EGRET data, covering all viewing periods through proposal cycle 4. Six 3EG catalog sources are reported here to display variability on short time scales; four of them are unidentified. In addition, three non-catalog variable sources are discussed.

Millennial-scale climate variations recorded in Early Pliocene colour reflectance time series from the lacustrine Ptolemais Basin (NW Greece)

NASA Astrophysics Data System (ADS)

Steenbrink, J.; Kloosterboer-van Hoeve, M. L.; Hilgen, F. J.

2003-03-01

Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub-Milankovitch cycles are still poorly understood, not least due to the complex feedback mechanisms of large ice sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well exposed in a series of open-pit lignite mines and exhibit a distinct millennial-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that resulted from precession-induced variations in climate. The higher-frequency, millennial-scale cyclicity is particularly prominent within the grey-coloured marl segment of individual cycles. A stratigraphic interval of ˜115 ka, covering five precession-induced sedimentary cycles, was studied in nine parallel sections from two open-pit lignite mines located several km apart. High-resolution colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environmental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of within-cycle variability at periods of ˜11, ˜5.5 and ˜2 ka. The occurrence of variability at such time scales at times before the intensification of the Northern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and Moon.

Testing our scenario of a failed wind for TW Hya

NASA Astrophysics Data System (ADS)

Guenther, Hans

2017-08-01

Young, accreting low-mass stars show strong, broad and asymmetric FUV emission lines. When multiple observations of the same wavelength region exist, we often see that the flux and profile of these lines change strongly between the observations. Observationally, this is poorly characterized, and theoretically, neither the lines profiles nor their variability can be explained. In 2011 we tried to remedy this situation by monitoring the classical Tauri star TW Hya for 10 orbits with HST/COS. At the time, the literature suggested that the variability could be due to a hot stellar wind and thus we distributed the observations over one month, which would have been the appropriate time scale. As it turns out, this assumption appears to have been wrong. The data we received clearly shows that no hot wind is present and that all variability happens on much shorter time scales. In this proposal, we show that we have done a thorough analysis of the existing data and we have a model to explain it. Now, we ask for additional monitoring of TW Hya to cover the time scale of a few hours - as we now know this is the relevant time scale to understand the variability.

Does the Nile reflect solar variability?

NASA Astrophysics Data System (ADS)

Ruzmaikin, Alexander; Feynman, Joan; Yung, Yuk

Historical records of the Nile water level provide a unique opportunity to investigate the possibility that solar variability influences the Earth's climate. Particularly important are the annual records of the water level, which are uninterrupted for the years 622-1470 A.D. These records are non-stationary, so that standard spectral analyses cannot adequately characterize them. Here the Empirical Mode Decomposition technique, which is designed to deal with non-stationary, nonlinear time series, becomes useful. It allows the identification of two characteristic time scales in the water level data that can be linked to solar variability: the 88 year period and a time scale of about 200 years. These time scales are also present in the concurrent aurora data. Auroras are driven by coronal mass ejections and the rate of auroras is an excellent proxy for solar variabiliy. Analysis of auroral data contemporaneous with the Nile data shows peaks at 88 years and about 200 years. This suggests a physical link between solar variability and the low-frequency variations of the Nile water level. The link involves the influence of solar variability on the North Annual Mode of atmospheric variability and its North Atlantic and Indian Oceans patterns that affect rainfall over Eastren Equatorial Africa where the Nile originates.

Compression based entropy estimation of heart rate variability on multiple time scales.

PubMed

Baumert, Mathias; Voss, Andreas; Javorka, Michal

2013-01-01

Heart rate fluctuates beat by beat in a complex manner. The aim of this study was to develop a framework for entropy assessment of heart rate fluctuations on multiple time scales. We employed the Lempel-Ziv algorithm for lossless data compression to investigate the compressibility of RR interval time series on different time scales, using a coarse-graining procedure. We estimated the entropy of RR interval time series of 20 young and 20 old subjects and also investigated the compressibility of randomly shuffled surrogate RR time series. The original RR time series displayed significantly smaller compression entropy values than randomized RR interval data. The RR interval time series of older subjects showed significantly different entropy characteristics over multiple time scales than those of younger subjects. In conclusion, data compression may be useful approach for multiscale entropy assessment of heart rate variability.

Exploring total cardiac variability in healthy and pathophysiological subjects using improved refined multiscale entropy.

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2017-02-01

Multiscale entropy (MSE) and refined multiscale entropy (RMSE) techniques are being widely used to evaluate the complexity of a time series across multiple time scales 't'. Both these techniques, at certain time scales (sometimes for the entire time scales, in the case of RMSE), assign higher entropy to the HRV time series of certain pathologies than that of healthy subjects, and to their corresponding randomized surrogate time series. This incorrect assessment of signal complexity may be due to the fact that these techniques suffer from the following limitations: (1) threshold value 'r' is updated as a function of long-term standard deviation and hence unable to explore the short-term variability as well as substantial variability inherited in beat-to-beat fluctuations of long-term HRV time series. (2) In RMSE, entropy values assigned to different filtered scaled time series are the result of changes in variance, but do not completely reflect the real structural organization inherited in original time series. In the present work, we propose an improved RMSE (I-RMSE) technique by introducing a new procedure to set the threshold value by taking into account the period-to-period variability inherited in a signal and evaluated it on simulated and real HRV database. The proposed I-RMSE assigns higher entropy to the age-matched healthy subjects than that of patients suffering from atrial fibrillation, congestive heart failure, sudden cardiac death and diabetes mellitus, for the entire time scales. The results strongly support the reduction in complexity of HRV time series in female group, old-aged, patients suffering from severe cardiovascular and non-cardiovascular diseases, and in their corresponding surrogate time series.

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.

Time-Structured and Net Intraindividual Variability: Tools for Examining the Development of Dynamic Characteristics and Processes

PubMed Central

Ram, Nilam; Gerstorf, Denis

2009-01-01

The study of intraindividual variability is the study of fluctuations, oscillations, adaptations, and “noise” in behavioral outcomes that manifest on micro-time scales. This paper provides a descriptive frame for the combined study of intraindividual variability and aging/development. At the conceptual level, we highlight that the study of intraindividual variability provides access to dynamic characteristics – construct-level descriptions of individuals' capacities for change (e.g., lability), and dynamic processes – the systematic changes individuals' exhibit in response to endogenous and exogenous influences (e.g., regulation). At the methodological level, we review how quantifications of net intraindividual variability (e.g., iSD) and models of time-structured intraindividual variability (e.g., time-series) are being used to measure and describe dynamic characteristics and processes. At the research design level, we point to the benefits of measurement burst study designs, wherein data are obtained across multiple time scales, for the study of development. PMID:20025395

Time-Variable Transit Time Distributions in the Hyporheic Zone of a Headwater Mountain Stream

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.

2018-03-01

Exchange of water between streams and their hyporheic zones is known to be dynamic in response to hydrologic forcing, variable in space, and to exist in a framework with nested flow cells. The expected result of heterogeneous geomorphic setting, hydrologic forcing, and between-feature interaction is hyporheic transit times that are highly variable in both space and time. Transit time distributions (TTDs) are important as they reflect the potential for hyporheic processes to impact biogeochemical transformations and ecosystems. In this study we simulate time-variable transit time distributions based on dynamic vertical exchange in a headwater mountain stream with observed, heterogeneous step-pool morphology. Our simulations include hyporheic exchange over a 600 m river corridor reach driven by continuously observed, time-variable hydrologic conditions for more than 1 year. We found that spatial variability at an instance in time is typically larger than temporal variation for the reach. Furthermore, we found reach-scale TTDs were marginally variable under all but the most extreme hydrologic conditions, indicating that TTDs are highly transferable in time. Finally, we found that aggregation of annual variation in space and time into a "master TTD" reasonably represents most of the hydrologic dynamics simulated, suggesting that this aggregation approach may provide a relevant basis for scaling from features or short reaches to entire networks.

Least-rattling feedback from strong time-scale separation

NASA Astrophysics Data System (ADS)

Chvykov, Pavel; England, Jeremy

2018-03-01

In most interacting many-body systems associated with some "emergent phenomena," we can identify subgroups of degrees of freedom that relax on dramatically different time scales. Time-scale separation of this kind is particularly helpful in nonequilibrium systems where only the fast variables are subjected to external driving; in such a case, it may be shown through elimination of fast variables that the slow coordinates effectively experience a thermal bath of spatially varying temperature. In this paper, we investigate how such a temperature landscape arises according to how the slow variables affect the character of the driven quasisteady state reached by the fast variables. Brownian motion in the presence of spatial temperature gradients is known to lead to the accumulation of probability density in low-temperature regions. Here, we focus on the implications of attraction to low effective temperature for the long-term evolution of slow variables. After quantitatively deriving the temperature landscape for a general class of overdamped systems using a path-integral technique, we then illustrate in a simple dynamical system how the attraction to low effective temperature has a fine-tuning effect on the slow variable, selecting configurations that bring about exceptionally low force fluctuation in the fast-variable steady state. We furthermore demonstrate that a particularly strong effect of this kind can take place when the slow variable is tuned to bring about orderly, integrable motion in the fast dynamics that avoids thermalizing energy absorbed from the drive. We thus point to a potentially general feedback mechanism in multi-time-scale active systems, that leads to the exploration of slow variable space, as if in search of fine tuning for a "least-rattling" response in the fast coordinates.

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.

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.

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling the properties of a long-range correlated process.

Contrasting scaling properties of interglacial and glacial climates

PubMed Central

Shao, Zhi-Gang; Ditlevsen, Peter D.

2016-01-01

Understanding natural climate variability is essential for assessments of climate change. This is reflected in the scaling properties of climate records. The scaling exponents of the interglacial and the glacial climates are fundamentally different. The Holocene record is monofractal, with a scaling exponent H∼0.7. On the contrary, the glacial record is multifractal, with a significantly higher scaling exponent H∼1.2, indicating a longer persistence time and stronger nonlinearities in the glacial climate. The glacial climate is dominated by the strong multi-millennial Dansgaard–Oeschger (DO) events influencing the long-time correlation. However, by separately analysing the last glacial maximum lacking DO events, here we find the same scaling for that period as for the full glacial period. The unbroken scaling thus indicates that the DO events are part of the natural variability and not externally triggered. At glacial time scales, there is a scale break to a trivial scaling, contrasting the DO events from the similarly saw-tooth-shaped glacial cycles. PMID:26980084

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Characterizing and understanding the climatic determinism of high- to low-frequency variations in precipitation in northwestern France using a coupled wavelet multiresolution/statistical downscaling approach

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Hannah, David; Lavers, David; Fossa, Manuel; Laignel, Benoit; Debret, Maxime

2017-04-01

Geophysical signals oscillate over several time-scales that explain different amount of their overall variability and may be related to different physical processes. Characterizing and understanding such variabilities in hydrological variations and investigating their determinism is one important issue in a context of climate change, as these variabilities can be occasionally superimposed to long-term trend possibly due to climate change. It is also important to refine our understanding of time-scale dependent linkages between large-scale climatic variations and hydrological responses on the regional or local-scale. Here we investigate such links by conducting a wavelet multiresolution statistical dowscaling approach of precipitation in northwestern France (Seine river catchment) over 1950-2016 using sea level pressure (SLP) and sea surface temperature (SST) as indicators of atmospheric and oceanic circulations, respectively. Previous results demonstrated that including multiresolution decomposition in a statistical downscaling model (within a so-called multiresolution ESD model) using SLP as large-scale predictor greatly improved simulation of low-frequency, i.e. interannual to interdecadal, fluctuations observed in precipitation. Building on these results, continuous wavelet transform of simulated precipiation using multiresolution ESD confirmed the good performance of the model to better explain variability at all time-scales. A sensitivity analysis of the model to the choice of the scale and wavelet function used was also tested. It appeared that whatever the wavelet used, the model performed similarly. The spatial patterns of SLP found as the best predictors for all time-scales, which resulted from the wavelet decomposition, revealed different structures according to time-scale, showing possible different determinisms. More particularly, some low-frequency components ( 3.2-yr and 19.3-yr) showed a much wide-spread spatial extentsion across the Atlantic. Moreover, in accordance with other previous studies, the wavelet components detected in SLP and precipitation on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation. Current works are now conducted including SST over the Atlantic in order to get further insights into this mechanism.

A propagating freshwater mode in the Arctic Ocean with multidecadal time scale

NASA Astrophysics Data System (ADS)

Schmith, Torben; Malskær Olsen, Steffen; Margrethe Ringgaard, Ida

2017-04-01

We apply Principal Oscillatory Pattern analysis to the Arctic Ocean fresh water content as simulated in a 500 year long control run with constant preindustrial forcing with the EC-Earth global climate model. Two modes emerge from this analysis. One mode is a standing mode with decadal time scale describing accumulation and release of fresh water in the Beaufort Gyre, known in the literature as the Beaufort Gyre flywheel. In addition, we identify a propagating mode with a time scale around 80 years, propagating along the rim of the Canadian Basin. This mode has maximum variability of the fresh water content in the Transpolar Drift and represents the bulk of the total variability of the fresh water content in the Arctic Ocean and also projects on the fresh water through the Fram Strait. Therefore, potentially, it can introduce a multidecadal variability to the Atlantic meridional overturning circulation. We will discuss the physical origin of this propagating mode. This include planetary-scale internal Rossby waves with multidecadal time scale, due to the slow variation of the Coriolis parameter at these high latitudes, as well as topographic steering of these Rossby waves.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

The GISS global climate-middle atmosphere model. II - Model variability due to interactions between planetary waves, the mean circulation and gravity wave drag

NASA Technical Reports Server (NTRS)

Rind, D.; Suozzo, R.; Balachandran, N. K.

1988-01-01

The variability which arises in the GISS Global Climate-Middle Atmosphere Model on two time scales is reviewed: interannual standard deviations, derived from the five-year control run, and intraseasonal variability as exemplified by statospheric warnings. The model's extratropical variability for both mean fields and eddy statistics appears reasonable when compared with observations, while the tropical wind variability near the stratopause may be excessive possibly, due to inertial oscillations. Both wave 1 and wave 2 warmings develop, with connections to tropospheric forcing. Variability on both time scales results from a complex set of interactions among planetary waves, the mean circulation, and gravity wave drag. Specific examples of these interactions are presented, which imply that variability in gravity wave forcing and drag may be an important component of the variability of the middle atmosphere.

Temporal dynamics of biogeochemical processes at the Norman Landfill site

USGS Publications Warehouse

Arora, Bhavna; Mohanty, Binayak P.; McGuire, Jennifer T.; Cozzarelli, Isabelle M.

2013-01-01

The temporal variability observed in redox sensitive species in groundwater can be attributed to coupled hydrological, geochemical, and microbial processes. These controlling processes are typically nonstationary, and distributed across various time scales. Therefore, the purpose of this study is to investigate biogeochemical data sets from a municipal landfill site to identify the dominant modes of variation and determine the physical controls that become significant at different time scales. Data on hydraulic head, specific conductance, δ2H, chloride, sulfate, nitrate, and nonvolatile dissolved organic carbon were collected between 1998 and 2000 at three wells at the Norman Landfill site in Norman, OK. Wavelet analysis on this geochemical data set indicates that variations in concentrations of reactive and conservative solutes are strongly coupled to hydrologic variability (water table elevation and precipitation) at 8 month scales, and to individual eco-hydrogeologic framework (such as seasonality of vegetation, surface-groundwater dynamics) at 16 month scales. Apart from hydrologic variations, temporal variability in sulfate concentrations can be associated with different sources (FeS cycling, recharge events) and sinks (uptake by vegetation) depending on the well location and proximity to the leachate plume. Results suggest that nitrate concentrations show multiscale behavior across temporal scales for different well locations, and dominant variability in dissolved organic carbon for a closed municipal landfill can be larger than 2 years due to its decomposition and changing content. A conceptual framework that explains the variability in chemical concentrations at different time scales as a function of hydrologic processes, site-specific interactions, and/or coupled biogeochemical effects is also presented.

Factors Affecting the Inter-annual to Centennial Time Scale Variability of All Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2016-04-01

The All Indian Summer Monsoon Rainfall (AISMR) is highly important for the livelihood of more than 1 billion people living in the Indian sub-continent. The agriculture of this region is heavily dependent on seasonal (JJAS) monsoon rainfall. An early start or a slight delay of monsoon, or an early withdrawal or prolonged monsoon season may upset the farmer's agricultural plans, can cause significant reduction in crop yield, and hence economic loss. Understanding of AISMR is also vital because it is a part of global atmospheric circulation system. Several studies show that AISMR is influenced by internal climate forcings (ICFs) viz. ENSO, AMO, PDO etc. as well as external climate forcings (ECFs) viz. Greenhouse Gases, volcanic eruptions, and Total Solar Irradiance (TSI). We investigate the influence of ICFs and ECFs on AISMR using recently developed statistical technique called De-trended Partial-Cross-Correlation Analysis (DPCCA). DPCCA can analyse a complex system of several interlinked variables. Often, climatic variables, being cross correlated, are simultaneously tele-connected with several other variables and it is not easy to isolate their intrinsic relationship. In the presence of non-stationarities and background signals the calculated correlation coefficients can be overestimated and erroneous. DPCCA method removes the non-stationarities and partials out the influence of background signals from the variables being cross correlated and thus give a robust estimate of correlation. We have performed the analysis using NOAA Reconstructed SSTs and homogenised instrumental AISMR data set from 1854-1999. By employing the DPCCA method we find that there is a statistically insignificant negative intrinsic relation (by excluding the influence of ICFs, and ECFs except TSI) between AISMR and TSI on decadal to centennial time scale. The ICFs considerably modulate the relation between AISMR and solar activity between 50-80 year time scales and transform this relationship to statistically significant positive. We conclude that the positive relation between AISMR and solar activity, as found by other authors, is due to the combined effect of AMO, PDO and multi-decadal ENSO variability on AISMR. The solar activity influences the ICFs and this influence is then transmitted to AISMR. Further, we find that there is statistically positive intrinsic relation between AISMR and AMO from 26 to 100 year time scales which is modulated by ICFs (PDO, ENSO) and ECFs. PDO, ENSO, and solar activity weaken this intrinsic relationship whereas the combined effect of ECFc (solar activity, volcanic eruptions, CO2, & tropospheric aerosol optical depth) results in strengthening of this relationship from 70 to 100 year time scales. There is a negative intrinsic relation between AISMR and PDO which is not statistically significant at any time scale. However this relationship becomes statistically significant only in the presence of combined effect of North Atlantic SSTs and ENSO (4-39 year time scale) and individual effect of TSI (3-26 year time scale) on AISMR. We also find that there is statistical significant negative relationship between AISMR and ENSO on inter-annual to centennial time scale and the strength of this relationship is modulated by solar activity from 3 to 40 year time scale.

Contrasting scaling properties of interglacial and glacial climates

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter; Shao, Zhi-Gang

2017-04-01

Understanding natural climate variability is essential for assessments of climate change. This is reflected in the scaling properties of climate records. The scaling exponents of the interglacial and the glacial climates are fundamentally different. The Holocene record is monofractal, with a scaling exponent H˜0.7. On the contrary, the glacial record is multifractal, with a significantly higher scaling exponent H˜1.2, indicating a longer persistence time and stronger nonlinearities in the glacial climate. The glacial climate is dominated by the strong multi-millennial Dansgaard-Oeschger (DO) events influencing the long-time correlation. However, by separately analysing the last glacial maximum lacking DO events, here we find the same scaling for that period as for the full glacial period. The unbroken scaling thus indicates that the DO events are part of the natural variability and not externally triggered. At glacial time scales, there is a scale break to a trivial scaling, contrasting the DO events from the similarly saw-tooth-shaped glacial cycles. Ref: Zhi-Gang Shao and Peter Ditlevsen, Nature Comm. 7, 10951, 2016

Environmental stochasticity controls soil erosion variability

PubMed Central

Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone

2016-01-01

Understanding soil erosion by water is essential for a range of research areas but the predictive skill of prognostic models has been repeatedly questioned because of scale limitations of empirical data and the high variability of soil loss across space and time scales. Improved understanding of the underlying processes and their interactions are needed to infer scaling properties of soil loss and better inform predictive methods. This study uses data from multiple environments to highlight temporal-scale dependency of soil loss: erosion variability decreases at larger scales but the reduction rate varies with environment. The reduction of variability of the geomorphic response is attributed to a ‘compensation effect’: temporal alternation of events that exhibit either source-limited or transport-limited regimes. The rate of reduction is related to environment stochasticity and a novel index is derived to reflect the level of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (enhanced predictability at the aggregated temporal scales) with respect to the mean hydrologic forcing, offering a promising indicator for estimating the degree of uncertainty of erosion assessments. PMID:26925542

Comparison of environmental forcings affecting suspended sediments variability in two macrotidal, highly-turbid estuaries

NASA Astrophysics Data System (ADS)

Jalón-Rojas, Isabel; Schmidt, Sabine; Sottolichio, Aldo

2017-11-01

The relative contribution of environmental forcing frequencies on turbidity variability is, for the first time, quantified at seasonal and multiannual time scales in tidal estuarine systems. With a decade of high-frequency, multi-site turbidity monitoring, the two nearby, macrotidal and highly-turbid Gironde and Loire estuaries (west France) are excellent natural laboratories for this purpose. Singular Spectrum Analyses, combined with Lomb-Scargle periodograms and Wavelet Transforms, were applied to the continuous multiannual turbidity time series. Frequencies of the main environmental factors affecting turbidity were identified: hydrological regime (high versus low river discharges), river flow variability, tidal range, tidal cycles, and turbulence. Their relative influences show similar patterns in both estuaries and depend on the estuarine region (lower or upper estuary) and the time scale (multiannual or seasonal). On the multiannual time scale, the relative contribution of tidal frequencies (tidal cycles and range) to turbidity variability decreases up-estuary from 68% to 47%, while the influence of river flow frequencies increases from 3% to 42%. On the seasonal time scale, the relative influence of forcings frequencies remains almost constant in the lower estuary, dominated by tidal frequencies (60% and 30% for tidal cycles and tidal range, respectively); in the upper reaches, it is variable depending on hydrological regime, even if tidal frequencies are responsible for up 50% of turbidity variance. These quantifications show the potential of combined spectral analyses to compare the behavior of suspended sediment in tidal estuaries throughout the world and to evaluate long-term changes in environmental forcings, especially in a context of global change. The relevance of this approach to compare nearby and overseas systems and to support management strategies is discussed (e.g., selection of effective operation frequencies/regions, prediction of the most affected regions by the implementation of operational management plans).

Overview of Sea-Ice Properties, Distribution and Temporal Variations, for Application to Ice-Atmosphere Chemical Processes.

NASA Astrophysics Data System (ADS)

Moritz, R. E.

2005-12-01

The properties, distribution and temporal variation of sea-ice are reviewed for application to problems of ice-atmosphere chemical processes. Typical vertical structure of sea-ice is presented for different ice types, including young ice, first-year ice and multi-year ice, emphasizing factors relevant to surface chemistry and gas exchange. Time average annual cycles of large scale variables are presented, including ice concentration, ice extent, ice thickness and ice age. Spatial and temporal variability of these large scale quantities is considered on time scales of 1-50 years, emphasizing recent and projected changes in the Arctic pack ice. The amount and time evolution of open water and thin ice are important factors that influence ocean-ice-atmosphere chemical processes. Observations and modeling of the sea-ice thickness distribution function are presented to characterize the range of variability in open water and thin ice.

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

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

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

Smoothing of millennial scale climate variability in European Loess (and other records)

NASA Astrophysics Data System (ADS)

Zeeden, Christian; Obreht, Igor; Hambach, Ulrich; Veres, Daniel; Marković, Slobodan B.; Lehmkuhl, Frank

2017-04-01

Millennial scale climate variability is seen in various records of the northern hemisphere in the last glacial cycle, and their expression represents a correlation tool beyond the resolution of e.g. luminescence dating. Highest (correlative) dating accuracy is a prerequisite of comparing different geoarchives, especially when related to archaeological findings. Here we attempt to constrain the timing of loess geoarchives representing the environmental context of early humans in south-eastern Europe, and discuss the challenge of dealing with smoothed records. In this contribution, we present rock magnetic and grain size data from the Rasova loess record in the Lower Danube basin (Romania), showing millennial scale climate variability. Additionally, we summarize similar data from the Lower and Middle Danube Basins. A comparison of these loess data and reference records from Greenland ice cores and the Mediterranean-Black Sea region indicates a rather unusual expression of millennial scale climate variability recorded in loess. To explain the observed patterns, we experiment with low-pass filters of reference records to simulate a signal smoothing by natural processes such as e.g. bioturbation and pervasive diagenesis. Low-pass filters avoid high frequency oscillations and focus on the longer period (lower frequency) variability, here using cut-off periods from 1-15 kyr. In our opinion low-pass filters represent simple models for the expression of millennial scale climate variability in low sedimentation environments, and in sediments where signals are smoothed by e.g. bioturbation and/or diagenesis. Using different low-pass filter thresholds allows us to (a) explain observed patterns and their relation to millennial scale climate variability, (b) propose these filtered/smoothed signals as correlation targets for records lacking millennial scale recording, but showing smoothed climate variability on supra-millennial scales, and (c) determine which time resolution specific (loess) records can reproduce. Comparing smoothed records to reference data may be a step forward especially for last glacial stratigraphies, where millennial scale patterns are certainly present but not directly recorded in some geoarchives. Interestingly, smoothed datasets from Greenland and the Black Sea-Mediterranean region are most similar in the last ca. 15 ka and again from ca. 30-50 ka. During the cold phase from ca. 30-15 ka records show dissimilarities, challenging robust correlative time scales in this age range. A potential explanation may be related to the expansion of Northern European and Alpine ice sheets influencing atmospheric systems in the North Atlantic and Eurasian regions and thus leading to regionally and temporally differentiated climatic responses.

Decadal- to Centennial-Scale Variations in Anchovy Biomass in the Last 250 Years Inferred From Scales Preserved in Laminated Sediments off the Coast of Pisco, Peru

NASA Astrophysics Data System (ADS)

Salvatteci, R.; Field, D.; Gutierrez, D.; Baumgartner, T.; Ferreira, V.; Velazco, F.; Niquen, M.; Guevara, R.; Sifeddine, A.; Ortlieb, L.

2005-12-01

The highly productive upwelling environment off the coast of Peru sustains one of the world's largest fisheries, the Peruvian anchoveta ( Engraulis ringens), but variability on interannual to decadal timescales results in dramatic variations in catch. We quantified variations in anchovy scale abundance preserved in laminated sediments collected at 300 m depth of the Peruvian margin (near Pisco, central Peru) to infer decadal- to centennial-scale population variability prior to the development of the fishery. High-resolution subsampling of 2.5 - 8.2 mm was done following the laminated structure of the core. A chronology based on downcore excess 210Pb activities and 14C-AMS ages indicate that samples represent an estimated 1-7 years in time. Anchovy scale deposition is correlated with anchovy landings at Pisco, indicating that scale deposition can be used as a proxy of (at least) local biomass. A small, but significant, reduction in anchovy scale width (0.2 mm) after the development of the fishery suggests a small effect of the fishery on anchovy size distributions. While decadal-scale variability in anchovy scale deposition is persistent throughout the record, a dramatic increase in scale flux occurred around 1860 A.D. and persists for approximately a century. Our results indicate that centennial-scale variability composes a large portion of the variability. However, decadal-scale variability associated with the Pacific Decadal Oscillation is not correlated with the inferred biomass variability prior to the development of the fishery. Shifts in the distribution of the population may account for an additional component of the variability in scale deposition.

Metabolic profiling reveals that time related physiological changes in mammalian cell perfusion cultures are bioreactor scale independent.

PubMed

Vernardis, Spyros I; Goudar, Chetan T; Klapa, Maria I

2013-09-01

Metabolic profiling was used to characterize the time course of cell physiology both in laboratory- and manufacturing-scale mammalian cell perfusion cultures. Two independent experiments were performed involving three vials from the same BHK cell bank, used to inoculate three laboratory-scale bioreactors, from which four manufacturing-scale cultures were initiated. It was shown that metabolomic analysis can indeed enhance the prime variable dataset for the monitoring of perfusion cultures by providing a higher resolution view of the metabolic state. Metabolic profiles could capture physiological state shifts over the course of the perfusion cultures and indicated a metabolic "signature" of the phase transitions, which was not observable from prime variable data. Specifically, the vast majority of metabolites had lower concentrations in the middle compared to the other two phases. Notably, metabolomics provided orthogonal (to prime variables) evidence that all cultures followed this same metabolic state shift with cell age, independently of bioreactor scale. © 2013 Elsevier Inc. All rights reserved.

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.

Variable order fractional Fokker-Planck equations derived from Continuous Time Random Walks

NASA Astrophysics Data System (ADS)

Straka, Peter

2018-08-01

Continuous Time Random Walk models (CTRW) of anomalous diffusion are studied, where the anomalous exponent β(x) ∈(0 , 1) varies in space. This type of situation occurs e.g. in biophysics, where the density of the intracellular matrix varies throughout a cell. Scaling limits of CTRWs are known to have probability distributions which solve fractional Fokker-Planck type equations (FFPE). This correspondence between stochastic processes and FFPE solutions has many useful extensions e.g. to nonlinear particle interactions and reactions, but has not yet been sufficiently developed for FFPEs of the "variable order" type with non-constant β(x) . In this article, variable order FFPEs (VOFFPE) are derived from scaling limits of CTRWs. The key mathematical tool is the 1-1 correspondence of a CTRW scaling limit to a bivariate Langevin process, which tracks the cumulative sum of jumps in one component and the cumulative sum of waiting times in the other. The spatially varying anomalous exponent is modelled by spatially varying β(x) -stable Lévy noise in the waiting time component. The VOFFPE displays a spatially heterogeneous temporal scaling behaviour, with generalized diffusivity and drift coefficients whose units are length2/timeβ(x) resp. length/timeβ(x). A global change of the time scale results in a spatially varying change in diffusivity and drift. A consequence of the mathematical derivation of a VOFFPE from CTRW limits in this article is that a solution of a VOFFPE can be approximated via Monte Carlo simulations. Based on such simulations, we are able to confirm that the VOFFPE is consistent under a change of the global time scale.

Two Centuries of Climate Variability From a Gulf of Papua Coral Confirms a Coherent, Widespread Multidecadal Signal

NASA Astrophysics Data System (ADS)

Cole, J. E.; Lough, J.; Reed, E. V.; Schrag, D. P.

2016-12-01

The Indo-Pacific warm pool is intimately involved with large-scale climate variability on seasonal to secular time scales. The lack of long instrumental observations in this region has motivated paleoclimatic analyses using diverse proxy data sources. We present here new multicentury paleoclimate records from a Gulf of Papua coral that capture past variability with a Pacific-wide signature. We have developed stable isotope, Sr/Ca, skeletal density, and luminescence data from a coral core recovered at Bramble Cay, Australia (9°S, 144°E). The geochemical records span CE 1775-1993 and are dominated by low-frequency (decade-century scale) variability that is consistent with records from other proxies in the same region, and with other coral records from far-flung sites across the southwest Pacific. Unlike in many Pacific coral records, we observe no strong trend towards warmer conditions. Although skeletal density bands are clearly visible, they show inconsistent seasonal phasing with the geochemical tracers of sea surface temperature (SST; Sr/Ca and oxygen isotope content), and skeletal density does not correlate with these tracers on longer time scales. In this coral, density banding must be controlled by a more complex mix of internal and/or external factors. Luminescent banding and reconstructed salinity provide similar histories, suggesting a common hydroclimatic signal with significant variability at periods of decades and longer. The strong low-frequency behavior in these new climate records of SST and hydroclimate, from a remote region of the Indo-Pacific, confirms an important source of internal climate variability, on a poorly documented time scale, from a region with far-reaching climatic importance.

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

Multi-time-scale X-ray reverberation mapping of accreting black holes

NASA Astrophysics Data System (ADS)

Mastroserio, Guglielmo; Ingram, Adam; van der Klis, Michiel

2018-04-01

Accreting black holes show characteristic reflection features in their X-ray spectrum, including an iron Kα line, resulting from hard X-ray continuum photons illuminating the accretion disc. The reverberation lag resulting from the path-length difference between direct and reflected emission provides a powerful tool to probe the innermost regions around both stellar-mass and supermassive black holes. Here, we present for the first time a reverberation mapping formalism that enables modelling of energy-dependent time lags and variability amplitude for a wide range of variability time-scales, taking the complete information of the cross-spectrum into account. We use a pivoting power-law model to account for the spectral variability of the continuum that dominates over the reverberation lags for longer time-scale variability. We use an analytic approximation to self-consistently account for the non-linear effects caused by this continuum spectral variability, which have been ignored by all previous reverberation studies. We find that ignoring these non-linear effects can bias measurements of the reverberation lags, particularly at low frequencies. Since our model is analytic, we are able to fit simultaneously for a wide range of Fourier frequencies without prohibitive computational expense. We also introduce a formalism of fitting to real and imaginary parts of our cross-spectrum statistic, which naturally avoids some mistakes/inaccuracies previously common in the literature. We perform proof-of-principle fits to Rossi X-ray Timing Explorer data of Cygnus X-1.

Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales.

PubMed

Silva, Luiz Eduardo Virgilio; Lataro, Renata Maria; Castania, Jaci Airton; Silva, Carlos Alberto Aguiar; Salgado, Helio Cesar; Fazan, Rubens; Porta, Alberto

2017-08-01

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains. NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV. Copyright © 2017 the American Physiological Society.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity. Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, R. V.; Potirakis, S. M.; Barbosa, S. M.; Matos, J. A. O.; Pereira, A. J. S. C.; Neves, L. J. P. F.

2015-05-01

The presence or absence of long-range correlations in the environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor radon concentrations from Coimbra, Portugal, each of which spans several weeks of continuous measurements at a high temporal resolution of five minutes.Our results reveal that at the study site, radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between some hours and one day) arising from marked periodic components, and (iii) low-frequency variability indicating a true long-range dependent process. In the presence of such multi-scale variability, common estimators of long-range memory in time series are prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

The Importance of Rotational Time-scales in Accretion Variability

NASA Astrophysics Data System (ADS)

Costigan, Gráinne; Vink, Joirck; Scholz, Aleks; Testi, Leonardo; Ray, Tom

2013-07-01

For the first few million years, one of the dominant sources of emission from a low mass young stellar object is from accretion. This process regulates the flow of material and angular moments from the surroundings to the central object, and is thought to play an important role in the definition of the long term stellar properties. Variability is a well documented attribute of accretion, and has been observed on time-scales of from days to years. However, where these variations come from is not clear. Th current model for accretion is magnetospheric accretion, where the stellar magnetic field truncates the disc, allowing the matter to flow from the disc onto the surface of the star. This model allows for variations in the accretion rate to come from many different sources, such as the magnetic field, the circumstellar disc and the interaction of the different parts of the system. We have been studying unbiased samples of accretors in order to identify the dominant time-scales and typical magnitudes of variations. In this way different sources of variations can be excluded and any missing physics in these systems identified. Through our previous work with the Long-term Accretion Monitoring Program (LAMP), we found 10 accretors in the ChaI region, whose variability is dominated by short term variations of 2 weeks. This was the shortest time period between spectroscopic observations which spanned 15 months, and rules out large scale processes in the disk as origins of this variability. On the basis of this study we have gone further to study the accretion signature H-alpha, over the time-scales of minutes and days in a set of Herbig Ae and T Tauri stars. Using the same methods as we used in LAMP we found the dominant time-scales of variations to be days. These samples both point towards rotation period of these objects as being an important time-scale for accretion variations. This allows us to indicate which are the most likely sources of these variations.

Space-time dependence between energy sources and climate related energy production

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Borga, Marco; Creutin, Jean-Dominique; Ramos, Maria-Helena; Tøfte, Lena; Warland, Geir

2014-05-01

The European Renewable Energy Directive adopted in 2009 focuses on achieving a 20% share of renewable energy in the EU overall energy mix by 2020. A major part of renewable energy production is related to climate, called "climate related energy" (CRE) production. CRE production systems (wind, solar, and hydropower) are characterized by a large degree of intermittency and variability on both short and long time scales due to the natural variability of climate variables. The main strategies to handle the variability of CRE production include energy-storage, -transport, -diversity and -information (smart grids). The three first strategies aim to smooth out the intermittency and variability of CRE production in time and space whereas the last strategy aims to provide a more optimal interaction between energy production and demand, i.e. to smooth out the residual load (the difference between demand and production). In order to increase the CRE share in the electricity system, it is essential to understand the space-time co-variability between the weather variables and CRE production under both current and future climates. This study presents a review of the literature that searches to tackle these problems. It reveals that the majority of studies deals with either a single CRE source or with the combination of two CREs, mostly wind and solar. This may be due to the fact that the most advanced countries in terms of wind equipment have also very little hydropower potential (Denmark, Ireland or UK, for instance). Hydropower is characterized by both a large storage capacity and flexibility in electricity production, and has therefore a large potential for both balancing and storing energy from wind- and solar-power. Several studies look at how to better connect regions with large share of hydropower (e.g., Scandinavia and the Alps) to regions with high shares of wind- and solar-power (e.g., green battery North-Sea net). Considering time scales, various studies consider wind and solar power production and their co-fluctuation at small time scales. The multi-scale nature of the variability is less studied, i.e., the potential adverse or favorable co-fluctuation at intermediate time scales involving water scarcity or abundance, is less present in the literature.Our review points out that it could be especially interesting to promote research on how the pronounced large-scale fluctuations in inflow to hydropower (intra-annual run-off) and smaller scale fluctuations in wind- and solar-power interact in an energy system. There is a need to better represent the profound difference between wind-, solar- and hydro-energy sources. On the one hand, they are all directly linked to the 2-D horizontal dynamics of meteorology. On the other hand, the branching structure of hydrological systems transforms this variability and governs the complex combination of natural inflows and reservoir storage.Finally, we note that the CRE production is, in addition to weather, also influenced by the energy system and market, i.e., the energy transport and demand across scales as well as changes of market regulation. The CRE production system lies thus in this nexus between climate, energy systems and market regulations. The work presented is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; http://www.complex.ac.uk)

Paleoecology and high-resolution paleohydrology of a kettle peatland in upper Michigan

NASA Astrophysics Data System (ADS)

Booth, Robert K.; Jackson, Stephen T.; Gray, Catherine E. D.

2004-01-01

We investigated the developmental and hydrological history of a Sphagnum-dominated, kettle peatland in Upper Michigan using testate amoebae, plant macrofossils, and pollen. Our primary objective was to determine if the paleohydrological record of the peatland represents a record of past climate variability at subcentennial to millennial time scales. To assess the role of millennial-scale climate variability on peatland paleohydrology, we compared the timing of peatland and upland vegetation changes. To investigate the role of higher-frequency climate variability on peatland paleohydrology, we used testate amoebae to reconstruct a high-resolution, hydrologic history of the peatland for the past 5100 years, and compared this record to other regional records of paleoclimate and vegetation. Comparisons revealed coherent patterns of hydrological, vegetational, and climatic changes, suggesting that peatland paleohydrology responded to climate variability at millennial to sub-centennial time scales. Although ombrotrophic peatlands have been the focus of most high-resolution peatland paleoclimate research, paleohydrological records from Sphagnum-dominated, closed-basin peatlands record high-frequency and low-magnitude climatic changes and thus represent a significant source of unexplored paleoclimate data.

Divergent phenological response to hydroclimate variability in forested mountain watersheds

Treesearch

Taehee Hwang; Lawrence E. Band; Chelcy F. Miniat; Conghe Song; Paul V . Bolstad; James M. Vose; Jason P. Love

2014-01-01

Mountain watersheds are primary sources of freshwater, carbon sequestration, and other ecosystem services. There is significant interest in the effects of climate change and variability on these processes over short to long time scales. Much of the impact of hydroclimate variability in forest ecosystems is manifested in vegetation dynamics in space and time. In steep...

The Oceanic Contribution to Atlantic Multi-Decadal Variability

NASA Astrophysics Data System (ADS)

Wills, R. C.; Armour, K.; Battisti, D. S.; Hartmann, D. L.

2017-12-01

Atlantic multi-decadal variability (AMV) is typically associated with variability in ocean heat transport (OHT) by the Atlantic Meridional Overturning Circulation (AMOC). However, recent work has cast doubt on this connection by showing that slab-ocean climate models, in which OHT cannot vary, exhibit similar variability. Here, we apply low-frequency component analysis to isolate the variability of Atlantic sea-surface temperatures (SSTs) that occurs on decadal and longer time scales. In observations and in pre-industrial control simulations of comprehensive climate models, we find that AMV is confined to the extratropics, with the strongest temperature anomalies in the North Atlantic subpolar gyre. We show that warm subpolar temperatures are associated with a strengthened AMOC, increased poleward OHT, and local heat fluxes from the ocean into the atmosphere. In contrast, the traditional index of AMV based on the basin-averaged SST anomaly shows warm temperatures preceded by heat fluxes from the atmosphere into the ocean, consistent with the atmosphere driving this variability, and shows a weak relationship with AMOC. The autocorrelation time of the basin-averaged SST index is 1 year compared to an autocorrelation time of 5 years for the variability of subpolar temperatures. This shows that multi-decadal variability of Atlantic SSTs is sustained by OHT variability associated with AMOC, while atmosphere-driven SST variability, such as exists in slab-ocean models, contributes primarily on interannual time scales.

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

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.

Estimation of surface heat and moisture fluxes over a prairie grassland. II - Two-dimensional time filtering and site variability

NASA Technical Reports Server (NTRS)

Crosson, William L.; Smith, Eric A.

1992-01-01

The behavior of in situ measurements of surface fluxes obtained during FIFE 1987 is examined by using correlative and spectral techniques in order to assess the significance of fluctuations on various time scales, from subdiurnal up to synoptic, intraseasonal, and annual scales. The objectives of this analysis are: (1) to determine which temporal scales have a significant impact on areal averaged fluxes and (2) to design a procedure for filtering an extended flux time series that preserves the basic diurnal features and longer time scales while removing high frequency noise that cannot be attributed to site-induced variation. These objectives are accomplished through the use of a two-dimensional cross-time Fourier transform, which serves to separate processes inherently related to diurnal and subdiurnal variability from those which impact flux variations on the longer time scales. A filtering procedure is desirable before the measurements are utilized as input with an experimental biosphere model, to insure that model based intercomparisons at multiple sites are uncontaminated by input variance not related to true site behavior. Analysis of the spectral decomposition indicates that subdiurnal time scales having periods shorter than 6 hours have little site-to-site consistency and therefore little impact on areal integrated fluxes.

Basic properties and variability

NASA Technical Reports Server (NTRS)

Querci, Francois R.

1987-01-01

Giant and supergiant M, S, and C stars are discussed in this survey of research. Basic properties as determined by spectra, chemical composition, photometry, or variability type are discussed. Space motions and space distributions of cool giants are described. Distribution of these stars in our galaxy and those nearby is discussed. Mira variables in particular are surveyed with emphasis on the following topics: (1) phase lag phenomenon; (2) Mira light curves; (3) variations in color indices; (4) determination of multiple periods; (5) correlations between quantities such as period length, light-curve shape, infrared (IR) excess, and visible and IR color diagram; (6) semiregular (SR) variables and different time scales in SR light variations; (7) irregular variable Lb and Lc stars; (8) different time-scale light variations; (9) hydrogen-deficient carbon (HdC) stars, in particular RCB stars; and (10) irreversible changes and rapid evolution in red variable stars.

Long-Term Variability of AGN at Hard X-Rays

NASA Technical Reports Server (NTRS)

Soldi, S.; Beckmann, V.; Baumgartner W. H.; Ponti, G.; Shrader, C. R.; Lubinski, P.; Krimm, H. A.; Mattana, F.; Tueller, J.

2013-01-01

Variability at all observed wavelengths is a distinctive property of active galactic nuclei (AGN). Hard X-rays provide us with a view of the innermost regions of AGN, mostly unbiased by absorption along the line of sight. Characterizing the intrinsic hard X-ray variability of a large AGN sample and comparing it to the results obtained at lower X-ray energies can significantly contribute to our understanding of the mechanisms underlying the high-energy radiation. Methods. Swift/BAT provides us with the unique opportunity to follow, on time scales of days to years and with a regular sampling, the 14-195 keV emission of the largest AGN sample available up to date for this kind of investigation. As a continuation of an early work on the first 9 months of BAT data, we study the amplitude of the variations, and their dependence on sub-class and on energy, for a sample of 110 radio quiet and radio loud AGN selected from the BAT 58-month survey. About 80 of the AGN in the sample are found to exhibit significant variability on months to years time scales, radio loud sources being the most variable. The amplitude of the variations and their energy dependence are incompatible with variability being driven at hard X-rays by changes of the absorption column density. In general, the variations in the 14-24 and 35-100 keV bands are well correlated, suggesting a common origin of the variability across the BAT energy band. However, radio quiet AGN display on average 10 larger variations at 14-24 keV than at 35-100 keV and a softer-when-brighter behavior for most of the Seyfert galaxies with detectable spectral variability on month time scale. In addition, sources with harder spectra are found to be more variable than softer ones. These properties are generally consistent with a variable power law continuum, in flux and shape, pivoting at energies 50 keV, to which a constant reflection component is superposed. When the same time scales are considered, the timing properties of AGN at hard X-rays are comparable to those at lower energies, with at least some of the differences possibly ascribable to components contributing differently in the two energy domains (e.g., reflection, absorption).

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity - Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios M.; Barbosa, Susana M.; Matos, Jose A. O.

2015-04-01

The presence or absence of long-range correlations in environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas Radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental Radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements at a high temporal resolution of five minutes. Our results reveal that at the study site, Radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between hours and one day) arising from marked periodic components probably related to tidal frequencies, and (iii) low-frequency variability indicating a true long-range dependent process, which might be dominated by a response to meteorological drivers. In the presence of such multi-scale variability, common estimators of long-range memory in time series are necessarily prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics. We emphasize that similar properties can be found in other types of geophysical time series (for example, tide gauge records), calling for a careful application of time series analysis tools when studying such data.

Intradaily variability of water quality in a shallow tidal lagoon: Mechanisms and implications

USGS Publications Warehouse

Lucas, L.V.; Sereno, D.M.; Burau, J.R.; Schraga, T.S.; Lopez, C.B.; Stacey, M.T.; Parchevsky, K.V.; Parchevsky, V.P.

2006-01-01

Although surface water quality and its underlying processes vary over time scales ranging from seconds to decades, they have historically been studied at the lower (weekly to interannual) frequencies. The aim of this study was to investigate intradaily variability of three water quality parameters in a small freshwater tidal lagoon (Mildred Island, California). High frequency time series of specific conductivity, water temperature, and chlorophyll a at two locations within the habitat were analyzed in conjunction with supporting hydrodynamic, meteorological, biological, and spatial mapping data. All three constituents exhibited large amplitude intradaily (e.g., semidiurnal tidal and diurnal) oscillations, and periodicity varied across constituents, space, and time. Like other tidal embayments, this habitat is influenced by several processes with distinct periodicities including physical controls, such as tides, solar radiation, and wind, and biological controls, such as photosynthesis, growth, and grazing. A scaling approach was developed to estimate individual process contributions to the observed variability. Scaling results were generally consistent with observations and together with detailed examination of time series and time derivatives, revealed specific mechanisms underlying the observed periodicities, including interactions between the tidal variability, heating, wind, and biology. The implications for monitoring were illustrated through subsampling of the data set. This exercise demonstrated how quantities needed by scientists and managers (e.g., mean or extreme concentrations) may be misrepresented by low frequency data and how short-duration high frequency measurements can aid in the design and interpretation of temporally coarser sampling programs. The dispersive export of chlorophyll a from the habitat exhibited a fortnightly variability corresponding to the modulation of semidiurnal tidal currents with the diurnal cycle of phytoplankton variability, demonstrating how high frequency interactions can govern long-term trends. Process identification, as through the scaling analysis here, can help us anticipate changes in system behavior and adapt our own interactions with the system. ?? 2006 Estuarine Research Federation.

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.

The effects of sampling frequency on the climate statistics of the European Centre for Medium-Range Weather Forecasts

NASA Astrophysics Data System (ADS)

Phillips, Thomas J.; Gates, W. Lawrence; Arpe, Klaus

1992-12-01

The effects of sampling frequency on the first- and second-moment statistics of selected European Centre for Medium-Range Weather Forecasts (ECMWF) model variables are investigated in a simulation of "perpetual July" with a diurnal cycle included and with surface and atmospheric fields saved at hourly intervals. The shortest characteristic time scales (as determined by the e-folding time of lagged autocorrelation functions) are those of ground heat fluxes and temperatures, precipitation and runoff, convective processes, cloud properties, and atmospheric vertical motion, while the longest time scales are exhibited by soil temperature and moisture, surface pressure, and atmospheric specific humidity, temperature, and wind. The time scales of surface heat and momentum fluxes and of convective processes are substantially shorter over land than over oceans. An appropriate sampling frequency for each model variable is obtained by comparing the estimates of first- and second-moment statistics determined at intervals ranging from 2 to 24 hours with the "best" estimates obtained from hourly sampling. Relatively accurate estimation of first- and second-moment climate statistics (10% errors in means, 20% errors in variances) can be achieved by sampling a model variable at intervals that usually are longer than the bandwidth of its time series but that often are shorter than its characteristic time scale. For the surface variables, sampling at intervals that are nonintegral divisors of a 24-hour day yields relatively more accurate time-mean statistics because of a reduction in errors associated with aliasing of the diurnal cycle and higher-frequency harmonics. The superior estimates of first-moment statistics are accompanied by inferior estimates of the variance of the daily means due to the presence of systematic biases, but these probably can be avoided by defining a different measure of low-frequency variability. Estimates of the intradiurnal variance of accumulated precipitation and surface runoff also are strongly impacted by the length of the storage interval. In light of these results, several alternative strategies for storage of the EMWF model variables are recommended.

Plague and Climate: Scales Matter

PubMed Central

Ben Ari, Tamara; Neerinckx, Simon; Gage, Kenneth L.; Kreppel, Katharina; Laudisoit, Anne; Leirs, Herwig; Stenseth, Nils Chr.

2011-01-01

Plague is enzootic in wildlife populations of small mammals in central and eastern Asia, Africa, South and North America, and has been recognized recently as a reemerging threat to humans. Its causative agent Yersinia pestis relies on wild rodent hosts and flea vectors for its maintenance in nature. Climate influences all three components (i.e., bacteria, vectors, and hosts) of the plague system and is a likely factor to explain some of plague's variability from small and regional to large scales. Here, we review effects of climate variables on plague hosts and vectors from individual or population scales to studies on the whole plague system at a large scale. Upscaled versions of small-scale processes are often invoked to explain plague variability in time and space at larger scales, presumably because similar scale-independent mechanisms underlie these relationships. This linearity assumption is discussed in the light of recent research that suggests some of its limitations. PMID:21949648

Spatial and Temporal Variability in Biogenic Gas Accumulation and Release in The Greater Everglades at Multiple Scales of Measurement

NASA Astrophysics Data System (ADS)

McClellan, M. D.; Cornett, C.; Schaffer, L.; Comas, X.

2017-12-01

Wetlands play a critical role in the carbon (C) cycle by producing and releasing significant amounts of greenhouse biogenic gasses (CO2, CH4) into the atmosphere. Wetlands in tropical and subtropical climates (such as the Florida Everglades) have become of great interest in the past two decades as they account for more than 20% of the global peatland C stock and are located in climates that favor year-round C emissions. Despite the increase in research involving C emission from these types of wetlands, the spatial and temporal variability involving C production, accumulation and release is still highly uncertain, and is the focus of this research at multiple scales of measurement (i.e. lab, field and landscape). Spatial variability in biogenic gas content, build up and release, at both the lab and field scales, was estimated using a series of ground penetrating radar (GPR) surveys constrained with gas traps fitted with time-lapse cameras. Variability in gas content was estimated at the sub-meter scale (lab scale) within two extracted monoliths from different wetland ecosystems at the Disney wilderness Preserve (DWP) and the Blue Cypress Preserve (BCP) using high frequency GPR (1.2 GHz) transects across the monoliths. At the field scale (> 10m) changes in biogenic gas content were estimated using 160 MHz GPR surveys collected within 4 different emergent wetlands at the DWP. Additionally, biogenic gas content from the extracted monoliths was used to developed a landscape comparison of C accumulation and emissions for each different wetland ecosystem. Changes in gas content over time were estimated at the lab scale at high temporal resolution (i.e. sub-hourly) in monoliths from the BCP and Water Conservation Area 1-A. An autonomous rail system was constructed to estimate biogenic gas content variability within the wetland soil matrix using a series of continuous, uninterrupted 1.2 GHz GPR transects along the samples. Measurements were again constrained with an array of gas traps fitted with time-lapse cameras. This research seeks to better understand the spatial and temporal variability of biogenic gas content within wetlands from the Greater Everglades Watershed. Such understanding may help to identify potential hotspots (both in space and time) and their implication for the flux estimates used as input in climate models.

Patterns in coupled water and energy cycle: Modeling, synthesis with observations, and assessing the subsurface-landsurface interactions

NASA Astrophysics Data System (ADS)

Rahman, A.; Kollet, S. J.; Sulis, M.

2013-12-01

In the terrestrial hydrological cycle, the atmosphere and the free groundwater table act as the upper and lower boundary condition, respectively, in the non-linear two-way exchange of mass and energy across the land surface. Identifying and quantifying the interactions among various atmospheric-subsurface-landsurface processes is complicated due to the diverse spatiotemporal scales associated with these processes. In this study, the coupled subsurface-landsurface model ParFlow.CLM was applied over a ~28,000 km2 model domain encompassing the Rur catchment, Germany, to simulate the fluxes of the coupled water and energy cycle. The model was forced by hourly atmospheric data from the COSMO-DE model (numerical weather prediction system of the German Weather Service) over one year. Following a spinup period, the model results were synthesized with observed river discharge, soil moisture, groundwater table depth, temperature, and landsurface energy flux data at different sites in the Rur catchment. It was shown that the model is able to reproduce reasonably the dynamics and also absolute values in observed fluxes and state variables without calibration. The spatiotemporal patterns in simulated water and energy fluxes as well as the interactions were studied using statistical, geostatistical and wavelet transform methods. While spatial patterns in the mass and energy fluxes can be predicted from atmospheric forcing and power law scaling in the transition and winter months, it appears that, in the summer months, the spatial patterns are determined by the spatially correlated variability in groundwater table depth. Continuous wavelet transform techniques were applied to study the variability of the catchment average mass and energy fluxes at varying time scales. From this analysis, the time scales associated with significant interactions among different mass and energy balance components were identified. The memory of precipitation variability in subsurface hydrodynamics acts at the 20-30 day time scale, while the groundwater contribution to sustain the long-term variability patterns in evapotranspiration acts at the 40-60 day scale. Diurnal patterns in connection with subsurface hydrodynamics were also detected. Thus, it appears that the subsurface hydrodynamics respond to the temporal patterns in land surface fluxes due to the variability in atmospheric forcing across multiple space and time scales.

Multiscale adaptive analysis of circadian rhythms and intradaily variability: Application to actigraphy time series in acute insomnia subjects

PubMed Central

Rivera, Ana Leonor; Toledo-Roy, Juan C.; Ellis, Jason; Angelova, Maia

2017-01-01

Circadian rhythms become less dominant and less regular with chronic-degenerative disease, such that to accurately assess these pathological conditions it is important to quantify not only periodic characteristics but also more irregular aspects of the corresponding time series. Novel data-adaptive techniques, such as singular spectrum analysis (SSA), allow for the decomposition of experimental time series, in a model-free way, into a trend, quasiperiodic components and noise fluctuations. We compared SSA with the traditional techniques of cosinor analysis and intradaily variability using 1-week continuous actigraphy data in young adults with acute insomnia and healthy age-matched controls. The findings suggest a small but significant delay in circadian components in the subjects with acute insomnia, i.e. a larger acrophase, and alterations in the day-to-day variability of acrophase and amplitude. The power of the ultradian components follows a fractal 1/f power law for controls, whereas for those with acute insomnia this power law breaks down because of an increased variability at the 90min time scale, reminiscent of Kleitman’s basic rest-activity (BRAC) cycles. This suggests that for healthy sleepers attention and activity can be sustained at whatever time scale required by circumstances, whereas for those with acute insomnia this capacity may be impaired and these individuals need to rest or switch activities in order to stay focused. Traditional methods of circadian rhythm analysis are unable to detect the more subtle effects of day-to-day variability and ultradian rhythm fragmentation at the specific 90min time scale. PMID:28753669

Solar variability: Implications for global change

NASA Technical Reports Server (NTRS)

Lean, Judith; Rind, David

1994-01-01

Solar variability is examined in search of implications for global change. The topics covered include the following: solar variation modification of global surface temperature; the significance of solar variability with respect to future climate change; and methods of reducing the uncertainty of the potential amplitude of solar variability on longer time scales.

The effect of atmospheric variability at intra-seasonal time scale on the SST of the Southwestern Atlantic Continental Shelf

NASA Astrophysics Data System (ADS)

Simionato, Claudia; Clara, Moira Luz; Jaureguizar, Andrés

2017-04-01

The Southwestern Atlantic Continental Shelf is characterized by large SST variability which origin remains unknown. In this work, we use blended SST data provided by NOAA CoastWatch Program, which combine the information coming from infrared and microwave sensors to provide daily images of an intermediate spatial resolution (11 km) with a noise floor of less than 0.2 °C. The data base starts at the middle of 2002, when an increase in signal variance is observed due to the fact that the Advanced Microwave Scanning Radiometer became available and as a consequence to its near all-weather coverage. Several years of observations are thus available, and even though the temporal and spatial resolution of these data is intermediate, they are reasonable for observing and characterizing the most significant patterns of SST variability in the (atmospheric) synoptic to intra-seasonal time scales, so as to help on understanding the physical processes which occur in the area and their forcing mechanisms. As we hypothesize that most of the variability in those time scales is wind forced, the study is complemented with the use of atmospheric observations -coming from remote sensing and reanalysis-. To perform the analysis, the long-term trend, inter-annual and seasonal variability are subtracted to the SST data to obtain the signal on intra-seasonal time scales. Then, Principal Components (EOF) analysis is applied to the data and composites of SST and several meteorological variables (wind, sea level pressure, air temperature, OLR, etc.) are computed for the days when the leading modes are active. It is found that the first three modes account for more than 70% of the variance. Modes 1 and 2 seem to be related to atmospheric waves generated in the tropical Pacific. Those waves, through atmospheric teleconnections, affect the SST on the southwestern South Atlantic Continental Shelf very rapidly. The oceanic anomalies exceed 0.7°C and are quite persistent. Mode 2 seems to be forced by an atmospheric 3-4 mode and might be related to SAM. Besides showing the impact of intra-seasonal atmospheric variability on the ocean at mid latitudes, the knowledge of the connections between the ocean and the atmosphere could aid on improving the ocean predictability on those time scales.

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

Satellite attitude prediction by multiple time scales method

NASA Technical Reports Server (NTRS)

Tao, Y. C.; Ramnath, R.

1975-01-01

An investigation is made of the problem of predicting the attitude of satellites under the influence of external disturbing torques. The attitude dynamics are first expressed in a perturbation formulation which is then solved by the multiple scales approach. The independent variable, time, is extended into new scales, fast, slow, etc., and the integration is carried out separately in the new variables. The theory is applied to two different satellite configurations, rigid body and dual spin, each of which may have an asymmetric mass distribution. The disturbing torques considered are gravity gradient and geomagnetic. Finally, as multiple time scales approach separates slow and fast behaviors of satellite attitude motion, this property is used for the design of an attitude control device. A nutation damping control loop, using the geomagnetic torque for an earth pointing dual spin satellite, is designed in terms of the slow equation.

Fine Scale Baleen Whale Behavior Observed Via Tagging Over Daily Time Scales

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Fine Scale Baleen Whale Behavior Observed Via Tagging...followed over time scales of days from an oceanographic vessel so that environmental sampling can be conducted in proximity to the tagged whale ...characterize the relationship between diel variability in the foraging behavior of baleen whales (North Atlantic right whales and sei whales ) and the

Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

NASA Astrophysics Data System (ADS)

Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.

2013-03-01

Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.

Evidence for the Maintenance of Slowly Varying Equatorial Currents by Intraseasonal Variability

NASA Astrophysics Data System (ADS)

Greatbatch, Richard J.; Claus, Martin; Brandt, Peter; Matthießen, Jan-Dirk; Tuchen, Franz Philip; Ascani, François; Dengler, Marcus; Toole, John; Roth, Christina; Farrar, J. Thomas

2018-02-01

Recent evidence from mooring data in the equatorial Atlantic reveals that semiannual and longer time scale ocean current variability is close to being resonant with equatorial basin modes. Here we show that intraseasonal variability, with time scales of tens of days, provides the energy to maintain these resonant basin modes against dissipation. The mechanism is analogous to that by which storm systems in the atmosphere act to maintain the atmospheric jet stream. We demonstrate the mechanism using an idealized model setup that exhibits equatorial deep jets. The results are supported by direct analysis of available mooring data from the equatorial Atlantic Ocean covering a depth range of several thousand meters. The analysis of the mooring data suggests that the same mechanism also helps maintain the seasonal variability.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-year predictability in a coupled general circulation model

NASA Astrophysics Data System (ADS)

Power, Scott; Colman, Rob

2006-02-01

Multi-year to decadal variability in a 100-year integration of a BMRC coupled atmosphere-ocean general circulation model (CGCM) is examined. The fractional contribution made by the decadal component generally increases with depth and latitude away from surface waters in the equatorial Indo-Pacific Ocean. The relative importance of decadal variability is enhanced in off-equatorial “ wings” in the subtropical eastern Pacific. The model and observations exhibit “ENSO-like” decadal patterns. Analytic results are derived, which show that the patterns can, in theory, occur in the absence of any predictability beyond ENSO time-scales. In practice, however, modification to this stochastic view is needed to account for robust differences between ENSO-like decadal patterns and their interannual counterparts. An analysis of variability in the CGCM, a wind-forced shallow water model, and a simple mixed layer model together with existing and new theoretical results are used to improve upon this stochastic paradigm and to provide a new theory for the origin of decadal ENSO-like patterns like the Interdecadal Pacific Oscillation and Pacific Decadal Oscillation. In this theory, ENSO-driven wind-stress variability forces internal equatorially-trapped Kelvin waves that propagate towards the eastern boundary. Kelvin waves can excite reflected internal westward propagating equatorially-trapped Rossby waves (RWs) and coastally-trapped waves (CTWs). CTWs have no impact on the off-equatorial sub-surface ocean outside the coastal wave guide, whereas the RWs do. If the frequency of the incident wave is too high, then only CTWs are excited. At lower frequencies, both CTWs and RWs can be excited. The lower the frequency, the greater the fraction of energy transmitted to RWs. This lowers the characteristic frequency (reddens the spectrum) of variability off the equator relative to its equatorial counterpart. At low frequencies, dissipation acts as an additional low pass filter that becomes more effective, as latitude increases. At the same time, ENSO-driven off-equatorial surface heating anomalies drive mixed layer temperature responses in both hemispheres. Both the eastern boundary interactions and the accumulation of surface heat fluxes by the surface mixed layer act to low pass filter the ENSO-forcing. The resulting off-equatorial variability is therefore more coherent with low pass filtered (decadal) ENSO indices [e.g. NINO3 sea-surface temperature (SST)] than with unfiltered ENSO indices. Consequently large correlations between variability and NINO3 extend further poleward on decadal time-scales than they do on interannual time-scales. This explains why decadal ENSO-like patterns have a broader meridional structure than their interannual counterparts. This difference in appearance can occur even if ENSO indices do not have any predictability beyond interannual time-scales. The wings around 15-20°S, and sub-surface variability at many other locations are predictable on interannual and multi-year time-scales. This includes westward propagating internal RWs within about 25° of the equator. The slowest of these take up to 4 years to reach the western boundary. This sub-surface predictability has significant oceanographic interest. However, it is linked to only low levels of SST variability. Consequently, extrapolation of delayed action oscillator theory to decadal time-scales might not be justified.

Millennial-scale Climate Variations Recorded As Far Back As The Early Pliocene

NASA Astrophysics Data System (ADS)

Steenbrink, J.; Hilgen, F. J.; Lourens, L. J.

Quaternary climate proxy records show compelling evidence for climate variability on time scales of a few thousand years. The causes for these millennial-scale or sub- Milankovitch cycles are yet poorly understood, not in the least due to the complex feedback mechanisms of large ice-sheets during the Quaternary. We present evidence of millennial-scale climate variability in Early Pliocene lacustrine sediments from the intramontane Ptolemais Basin in northwestern Greece. The sediments are well ex- posed in a series of open-pit lignite mines and exhibit a distinct m-scale sedimentary cyclicity of alternating lignites and lacustrine marl beds that result from precession- induced variations in climate. A higher-frequency cyclicity is particular prominent within the marl segment of individual cycles. A stratigraphic interval of~115 kyr, cov- ering five precession-induced sedimentary cycles, was studied in nine parallel sections from two quarries located several km apart. Colour reflectance records were used to quantify the within-cycle variability and to determine its lateral continuity. Much of the within-cycle variability could be correlated between the parallel sections, even in fine detail, which suggests that these changes reflect basin-wide variations in environ- mental conditions related to (regional) climate fluctuations. Interbedded volcanic ash beds demonstrate the synchronicity of these fluctuations and spectral analysis of the reflectance time series shows a significant concentration of variability at periods of ~11,~5.5 and~2 kyr. Their occurrence at times before the intensification of the North- ern Hemisphere glaciation suggests that they cannot solely have resulted from internal ice-sheet dynamics. Possible candidates include harmonics or combination tones of the main orbital cycles, variations in solar output or periodic motions of the Earth and moon.

A VLA (Very Large Array) Search for 5 GHz Radio Transients and Variables at Low Galactic Latitudes

NASA Technical Reports Server (NTRS)

Ofek, E. O.; Frail, D. A.; Breslauer, B.; Kulkarni, S. R.; Chandra, P.; Gal-Yam, A.; Kasliwal, M. M.; Gehrels, N.

2012-01-01

We present the results of a 5GHz survey with the Very Large Array (VLA) and the expanded VLA, designed to search for short-lived (approx < 1 day) transients and to characterize the variability of radio sources at milli-Jansky levels. A total sky area of 2.66 sq. deg, spread over 141 fields at low Galactic latitudes (b approx equals 6 - 8 deg) was observed 16 times with a cadence that was chosen to sample timescales of days, months and years. Most of the data were reduced, analyzed and searched for transients in near real time. Interesting candidates were followed up using visible light telescopes (typical delays of 1 - 2 hr) and the X-Ray Telescope on board the Swift satellite. The final processing of the data revealed a single possible transient with a flux density of f(sub v) approx equals 2.4mJy. This implies a transients sky surface density of kappa(f(sub v) > 1.8mJy) = 0.039(exp +0.13,+0.18) (sub .0.032,.0.038) / sq. deg (1, 2 sigma confidence errors). This areal density is consistent with the sky surface density of transients from the Bower et al. survey extrapolated to 1.8mJy. Our observed transient areal density is consistent with a Neutron Stars (NSs) origin for these events. Furthermore, we use the data to measure the sources variability on days to years time scales, and we present the variability structure function of 5GHz sources. The mean structure function shows a fast increase on approximately 1 day time scale, followed by a slower increase on time scales of up to 10 days. On time scales between 10 - 60 days the structure function is roughly constant. We find that approx > 30% of the unresolved sources brighter than 1.8mJy are variable at the > 4-sigma confidence level, presumably due mainly to refractive scintillation.

Long and short term variability of seven blazars in six near-infrared/optical bands

NASA Astrophysics Data System (ADS)

Sandrinelli, A.; Covino, S.; Treves, A.

2014-02-01

Context. We present the light curves of six BL Lac objects, PKS 0537-441, PKS 0735+17, OJ 287, PKS 2005-489, PKS 2155-304, and W Comae, and of the flat spectrum radio quasar PKS 1510-089, as a part of a photometric monitoring program in the near-infrared/optical bands started in 2004. All sources are Fermi blazars. Aims: Our purpose is to investigate flux and spectral variability on short and long time scales. Systematic monitoring, independent of the activity of the source, guarantees large sample size statistics, and allows an unbiased view of different activity states on weekly or daily time scales for the whole timeframe and on nightly time scales for some epochs. Methods: Data were obtained with the REM telescope located at the ESO premises of La Silla (Chile). Light curves were gathered in the optical/near-infrared VRIJHK bands from April 2005 to June 2012. Results: Variability ≳3 mag is observed in PKS 0537-441, PKS 1510-089 and PKS 2155-304, the largest ranges spanned in the near-infrared. The color intensity plots show rather different morphologies. The spectral energy distributions in general are well fitted by a power law, with some deviations that are more apparent in low states. Some variability episodes during a night interval are well documented for PKS 0537-441 and PKS 2155-304. For the latter source the variability time scale implies a large relativistic beaming factor. Full Table 3 is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/562/A79

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

Using Derivative Estimates to Describe Intraindividual Variability at Multiple Time Scales

ERIC Educational Resources Information Center

Deboeck, Pascal R.; Montpetit, Mignon A.; Bergeman, C. S.; Boker, Steven M.

2009-01-01

The study of intraindividual variability is central to the study of individuals in psychology. Previous research has related the variance observed in repeated measurements (time series) of individuals to traitlike measures that are logically related. Intraindividual measures, such as intraindividual standard deviation or the coefficient of…

Probing AGN Accretion Physics through AGN Variability: Insights from Kepler

NASA Astrophysics Data System (ADS)

Kasliwal, Vishal Pramod

Active Galactic Nuclei (AGN) exhibit large luminosity variations over the entire electromagnetic spectrum on timescales ranging from hours to years. The variations in luminosity are devoid of any periodic character and appear stochastic. While complex correlations exist between the variability observed in different parts of the electromagnetic spectrum, no frequency band appears to be completely dominant, suggesting that the physical processes producing the variability are exceedingly rich and complex. In the absence of a clear theoretical explanation of the variability, phenomenological models are used to study AGN variability. The stochastic behavior of AGN variability makes formulating such models difficult and connecting them to the underlying physics exceedingly hard. We study AGN light curves serendipitously observed by the NASA Kepler planet-finding mission. Compared to previous ground-based observations, Kepler offers higher precision and a smaller sampling interval resulting in potentially higher quality light curves. Using structure functions, we demonstrate that (1) the simplest statistical model of AGN variability, the damped random walk (DRW), is insufficient to characterize the observed behavior of AGN light curves; and (2) variability begins to occur in AGN on time-scales as short as hours. Of the 20 light curves studied by us, only 3-8 may be consistent with the DRW. The structure functions of the AGN in our sample exhibit complex behavior with pronounced dips on time-scales of 10-100 d suggesting that AGN variability can be very complex and merits further analysis. We examine the accuracy of the Kepler pipeline-generated light curves and find that the publicly available light curves may require re-processing to reduce contamination from field sources. We show that while the re-processing changes the exact PSD power law slopes inferred by us, it is unlikely to change the conclusion of our structure function study-Kepler AGN light curves indicate that the DRW is insufficient to characterize AGN variability. We provide a new approach to probing accretion physics with variability by decomposing observed light curves into a set of impulses that drive diffusive processes using C-ARMA models. Applying our approach to Kepler data, we demonstrate how the time-scales reported in the literature can be interpreted in the context of the growth and decay time-scales for flux perturbations and tentatively identify the flux perturbation driving process with accretion disk turbulence on length-scales much longer than the characteristic eddy size. Our analysis technique is applicable to (1) studying the connection between AGN sub-type and variability properties; (2) probing the origins of variability by studying the multi-wavelength behavior of AGN; (3) testing numerical simulations of accretion flows with the goal of creating a library of the variability properties of different accretion mechanisms; (4) hunting for changes in the behavior of the accretion flow by block-analyzing observed light curves; and (5) constraining the sampling requirements of future surveys of AGN variability.

Palaeoclimate dynamics : a voyage through scales

NASA Astrophysics Data System (ADS)

Crucifix, Michel; Mitsui, Takahito

2015-04-01

Our knowledge of climate dynamics depends on indirect observations of past climate evolution, as well as on what can be inferred from theoretical arguments. At the scale of the Cenozoic, it is common to define a framework of nested time scales, the longest time scale of interest being related to the slow tectonic evolution, then variability associated with or controlled by the astronomical forcing, and finally the fastest dynamics associated with the natural modes of variability of the ocean and the atmosphere. For example, in a model, the astronomical modes of variability may be simulated with deterministic equations under fixed boundary conditions representing the tectonic state, and associated with stochastic parameterisations of the ocean-atmosphere (chaotic) modes of motion. Bifurcations or, more generally, qualitative changes in climate dynamics may be scanned by changing slowly the tectonic state, in order to provide explanations to observed changes in regimes such as the appearance of ice ages and their changes in length or amplitude. The above framework, largely theorized by B. Saltzman, may still be partly justified but is in need of a review. We address here specifically three questions: To what extent astronomical variability interacts with natural modes of ocean - atmosphere variability ? Specifically, how does millennial variability (e.g.: Dansgaard-Oeschger events) fit the Saltzman scheme ? The astronomical forcing is quasi-periodic, and we recently showed that it may produce somewhat counter-intuitive dynamics associated with the emergence of strange non-chaotic attractors. What are the consequences on the spectrum of climate variability ? What are the effects of centennial climate variability on the slow variability of climate ? These three questions are addressed by reference to recently published material, with the objective of emphasising research questions to be explored in the near future.

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.

Centennial-scale winter climate variability over the last two millennia in the northern Gulf of Mexico based on paired δ18O and Mg/Ca in Globorotalia truncatulinoides

NASA Astrophysics Data System (ADS)

Fortiz, V.; Thirumalai, K.; Richey, J. N.; Quinn, T. M.

2014-12-01

We present a replicated record of paired foraminiferal δ18O and Mg/Ca variations in multi-cores collected from the Garrison Basin (26º43'N, 93º55'W) in the northern Gulf of Mexico (GOM). Using δ18O (sea surface temperature, SST; sea surface salinity, SSS proxy) and Mg/Ca (SST proxy) variations in non-encrusted planktic foraminifer Globorotalia truncatulinoides we produce time series spanning the last two millennia that is characterized by centennial-scale climate variability. We interpret geochemical variations in G. truncatulinoides to reflect winter climate variability because data from a sediment trap, located ~350 km east of the core site, reveal that annual flux of G. truncatulinoides is heavily weighted towards winter (peak production in January-February; Spear et al., 2011). Similar centennial-scale variability is also observed in the foraminiferal geochemistry of Globigerinoides ruber in the same multi-cores, which likely reflect mean annual climate variations. Our replicated results and comparisons to other SST reconstructions from the region lend confidence that the northern GOM surface ocean underwent large, centennial-scale variability, most likely dominated by changes in winter climate. This variability occurred in a time period where climate forcing is small and background conditions are similar to pre-industrial times. References: Spear, J.W.; Poore, R.Z., and Quinn, T.M., 2011, Globorotalia truncatulinoides (dextral) Mg/Ca as a proxy for Gulf of Mexico winter mixed-layer temperature: Evidence from a sediment trap in the northern Gulf of Mexico. Marine Micropaleontology, 80, 53-61.

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

Nottale, Laurent; Célérier, Marie-Noëlle

One of the main results of scale relativity as regards the foundation of quantum mechanics is its explanation of the origin of the complex nature of the wave function. The scale relativity theory introduces an explicit dependence of physical quantities on scale variables, founding itself on the theorem according to which a continuous and non-differentiable space-time is fractal (i.e., scale-divergent). In the present paper, the nature of the scale variables and their relations to resolutions and differential elements are specified in the non-relativistic case (fractal space). We show that, owing to the scale-dependence which it induces, non-differentiability involves a fundamentalmore » two-valuedness of the mean derivatives. Since, in the scale relativity framework, the wave function is a manifestation of the velocity field of fractal space-time geodesics, the two-valuedness of velocities leads to write them in terms of complex numbers, and yields therefore the complex nature of the wave function, from which the usual expression of the Schrödinger equation can be derived.« less

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

On the upscaling of process-based models in deltaic applications

NASA Astrophysics Data System (ADS)

Li, L.; Storms, J. E. A.; Walstra, D. J. R.

2018-03-01

Process-based numerical models are increasingly used to study the evolution of marine and terrestrial depositional environments. Whilst a detailed description of small-scale processes provides an accurate representation of reality, application on geological timescales is restrained by the associated increase in computational time. In order to reduce the computational time, a number of acceleration methods are combined and evaluated for a schematic supply-driven delta (static base level) and an accommodation-driven delta (variable base level). The performance of the combined acceleration methods is evaluated by comparing the morphological indicators such as distributary channel networking and delta volumes derived from the model predictions for various levels of acceleration. The results of the accelerated models are compared to the outcomes from a series of simulations to capture autogenic variability. Autogenic variability is quantified by re-running identical models on an initial bathymetry with 1 cm added noise. The overall results show that the variability of the accelerated models fall within the autogenic variability range, suggesting that the application of acceleration methods does not significantly affect the simulated delta evolution. The Time-scale compression method (the acceleration method introduced in this paper) results in an increased computational efficiency of 75% without adversely affecting the simulated delta evolution compared to a base case. The combination of the Time-scale compression method with the existing acceleration methods has the potential to extend the application range of process-based models towards geologic timescales.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

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.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

An extensive spectroscopic time series of three Wolf-Rayet stars - I. The lifetime of large-scale structures in the wind of WR 134

NASA Astrophysics Data System (ADS)

Aldoretta, E. J.; St-Louis, N.; Richardson, N. D.; Moffat, A. F. J.; Eversberg, T.; Hill, G. M.; Shenar, T.; Artigau, É.; Gauza, B.; Knapen, J. H.; Kubát, J.; Kubátová, B.; Maltais-Tariant, R.; Muñoz, M.; Pablo, H.; Ramiaramanantsoa, T.; Richard-Laferrière, A.; Sablowski, D. P.; Simón-Díaz, S.; St-Jean, L.; Bolduan, F.; Dias, F. M.; Dubreuil, P.; Fuchs, D.; Garrel, T.; Grutzeck, G.; Hunger, T.; Küsters, D.; Langenbrink, M.; Leadbeater, R.; Li, D.; Lopez, A.; Mauclaire, B.; Moldenhawer, T.; Potter, M.; dos Santos, E. M.; Schanne, L.; Schmidt, J.; Sieske, H.; Strachan, J.; Stinner, E.; Stinner, P.; Stober, B.; Strandbaek, K.; Syder, T.; Verilhac, D.; Waldschläger, U.; Weiss, D.; Wendt, A.

2016-08-01

During the summer of 2013, a 4-month spectroscopic campaign took place to observe the variabilities in three Wolf-Rayet stars. The spectroscopic data have been analysed for WR 134 (WN6b), to better understand its behaviour and long-term periodicity, which we interpret as arising from corotating interaction regions (CIRs) in the wind. By analysing the variability of the He II λ5411 emission line, the previously identified period was refined to P = 2.255 ± 0.008 (s.d.) d. The coherency time of the variability, which we associate with the lifetime of the CIRs in the wind, was deduced to be 40 ± 6 d, or ˜18 cycles, by cross-correlating the variability patterns as a function of time. When comparing the phased observational grey-scale difference images with theoretical grey-scales previously calculated from models including CIRs in an optically thin stellar wind, we find that two CIRs were likely present. A separation in longitude of Δφ ≃ 90° was determined between the two CIRs and we suggest that the different maximum velocities that they reach indicate that they emerge from different latitudes. We have also been able to detect observational signatures of the CIRs in other spectral lines (C IV λλ5802,5812 and He I λ5876). Furthermore, a DAC was found to be present simultaneously with the CIR signatures detected in the He I λ5876 emission line which is consistent with the proposed geometry of the large-scale structures in the wind. Small-scale structures also show a presence in the wind, simultaneously with the larger scale structures, showing that they do in fact co-exist.

Atmospheric forcing of the upper ocean transport in the Gulf of Mexico: From seasonal to diurnal scales

NASA Astrophysics Data System (ADS)

Judt, Falko; Chen, Shuyi S.; Curcic, Milan

2016-06-01

The 2010 Deepwater Horizon oil spill in the Gulf of Mexico (GoM) was an environmental disaster, which highlighted the urgent need to predict the transport and dispersion of hydrocarbon. Although the variability of the atmospheric forcing plays a major role in the upper ocean circulation and transport of the pollutants, the air-sea interaction on various time scales is not well understood. This study provides a comprehensive overview of the atmospheric forcing and upper ocean response in the GoM from seasonal to diurnal time scales, using climatologies derived from long-term observations, in situ observations from two field campaigns, and a coupled model. The atmospheric forcing in the GoM is characterized by striking seasonality. In the summer, the time-average large-scale forcing is weak, despite occasional extreme winds associated with hurricanes. In the winter, the atmospheric forcing is much stronger, and dominated by synoptic variability on time scales of 3-7 days associated with winter storms and cold air outbreaks. The diurnal cycle is more pronounced during the summer, when sea breeze circulations affect the coastal regions and nighttime wind maxima occur over the offshore waters. Realtime predictions from a high-resolution atmosphere-wave-ocean coupled model were evaluated for both summer and winter conditions during the Grand LAgrangian Deployment (GLAD) in July-August 2012 and the Surfzone Coastal Oil Pathways Experiment (SCOPE) in November-December 2013. The model generally captured the variability of atmospheric forcing on all scales, but suffered from some systematic errors.

A deep X-ray view of the bare AGN Ark 120. III. X-ray timing analysis and multiwavelength variability

NASA Astrophysics Data System (ADS)

Lobban, A. P.; Porquet, D.; Reeves, J. N.; Markowitz, A.; Nardini, E.; Grosso, N.

2018-03-01

We present the spectral/timing properties of the bare Seyfert galaxy Ark 120 through a deep ˜420 ks XMM-Newton campaign plus recent NuSTAR observations and a ˜6-month Swift monitoring campaign. We investigate the spectral decomposition through fractional rms, covariance and difference spectra, finding the mid- to long-time-scale (˜day-year) variability to be dominated by a relatively smooth, steep component, peaking in the soft X-ray band. Additionally, we find evidence for variable Fe K emission redward of the Fe Kα core on long time-scales, consistent with previous findings. We detect a clearly defined power spectrum which we model with a power law with a slope of α ˜ 1.9. By extending the power spectrum to lower frequencies through the inclusion of Swift and Rossi X-ray Timing Explorer data, we find tentative evidence of a high-frequency break, consistent with existing scaling relations. We also explore frequency-dependent Fourier time lags, detecting a negative (`soft') lag for the first time in this source with the 0.3-1 keV band lagging behind the 1-4 keV band with a time delay, τ, of ˜900 s. Finally, we analyse the variability in the optical and ultraviolet (UV) bands using the Optical/UV Monitor onboard XMM-Newton and the Ultra-Violet/Optical Telescope onboard Swift and search for time-dependent correlations between the optical/UV/X-ray bands. We find tentative evidence for the U-band emission lagging behind the X-rays with a time delay of τ = 2.4 ± 1.8 d, which we discuss in the context of disc reprocessing.

Holocene multidecadal- to millennial-scale variations in Iceland-Scotland overflow and their relationship to climate

NASA Astrophysics Data System (ADS)

Mjell, Tor Lien; Ninnemann, Ulysses S.; Eldevik, Tor; Kleiven, Helga Kikki F.

2015-05-01

The Nordic Seas overflows are an important part of the Atlantic thermohaline circulation. While there is growing evidence that the overflow of dense water changed on orbital time scales during the Holocene, less is known about the variability on shorter time scales beyond the instrumental record. Here we reconstruct the relative changes in flow strength of Iceland-Scotland Overflow Water (ISOW), the eastern branch of the overflows, on multidecadal-millennial time scales. The reconstruction is based on mean sortable silt (SS>¯) from a sediment core on the Gardar Drift (60°19'N, 23°58'W, 2081 m). Our SS>¯ record reveals that the main variance in ISOW vigor occurred on millennial time scales (1-2 kyr) with particularly prominent fluctuations after 8 kyr. Superimposed on the millennial variability, there were multidecadal-centennial flow speed fluctuations during the early Holocene (10-9 kyr) and one prominent minimum at 0.9 kyr. We find a broad agreement between reconstructed ISOW and regional North Atlantic climate, where a strong (weak) ISOW is generally associated with warm (cold) climate. We further identify the possible contribution of anomalous heat and freshwater forcing, respectively, related to reconstructed overflow variability. We infer that ocean poleward heat transport can explain the relationship between regional climate and ISOW during the middle to late Holocene, whereas freshwater input provides a possible explanation for the reduced overflow during early Holocene (8-10 kyr).

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

Describing temporal variability of the mean Estonian precipitation series in climate time scale

NASA Astrophysics Data System (ADS)

Post, P.; Kärner, O.

2009-04-01

Applicability of the random walk type models to represent the temporal variability of various atmospheric temperature series has been successfully demonstrated recently (e.g. Kärner, 2002). Main problem in the temperature modeling is connected to the scale break in the generally self similar air temperature anomaly series (Kärner, 2005). The break separates short-range strong non-stationarity from nearly stationary longer range variability region. This is an indication of the fact that several geophysical time series show a short-range non-stationary behaviour and a stationary behaviour in longer range (Davis et al., 1996). In order to model series like that the choice of time step appears to be crucial. To characterize the long-range variability we can neglect the short-range non-stationary fluctuations, provided that we are able to model properly the long-range tendencies. The structure function (Monin and Yaglom, 1975) was used to determine an approximate segregation line between the short and the long scale in terms of modeling. The longer scale can be called climate one, because such models are applicable in scales over some decades. In order to get rid of the short-range fluctuations in daily series the variability can be examined using sufficiently long time step. In the present paper, we show that the same philosophy is useful to find a model to represent a climate-scale temporal variability of the Estonian daily mean precipitation amount series over 45 years (1961-2005). Temporal variability of the obtained daily time series is examined by means of an autoregressive and integrated moving average (ARIMA) family model of the type (0,1,1). This model is applicable for daily precipitation simulating if to select an appropriate time step that enables us to neglet the short-range non-stationary fluctuations. A considerably longer time step than one day (30 days) is used in the current paper to model the precipitation time series variability. Each ARIMA (0,1,1) model can be interpreted to be consisting of random walk in a noisy environment (Box and Jenkins, 1976). The fitted model appears to be weakly non-stationary, that gives us the possibility to use stationary approximation if only the noise component from that sum of white noise and random walk is exploited. We get a convenient routine to generate a stationary precipitation climatology with a reasonable accuracy, since the noise component variance is much larger than the dispersion of the random walk generator. This interpretation emphasizes dominating role of a random component in the precipitation series. The result is understandable due to a small territory of Estonia that is situated in the mid-latitude cyclone track. References Box, J.E.P. and G. Jenkins 1976: Time Series Analysis, Forecasting and Control (revised edn.), Holden Day San Francisco, CA, 575 pp. Davis, A., Marshak, A., Wiscombe, W. and R. Cahalan 1996: Multifractal characterizations of intermittency in nonstationary geophysical signals and fields.in G. Trevino et al. (eds) Current Topics in Nonsstationarity Analysis. World-Scientific, Singapore, 97-158. Kärner, O. 2002: On nonstationarity and antipersistency in global temperature series. J. Geophys. Res. D107; doi:10.1029/2001JD002024. Kärner, O. 2005: Some examples on negative feedback in the Earth climate system. Centr. European J. Phys. 3; 190-208. Monin, A.S. and A.M. Yaglom 1975: Statistical Fluid Mechanics, Vol 2. Mechanics of Turbulence , MIT Press Boston Mass, 886 pp.

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multi-time Scale Coordination of Distributed Energy Resources in Isolated Power Systems

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

Mayhorn, Ebony; Xie, Le; Butler-Purry, Karen

2016-03-31

In isolated power systems, including microgrids, distributed assets, such as renewable energy resources (e.g. wind, solar) and energy storage, can be actively coordinated to reduce dependency on fossil fuel generation. The key challenge of such coordination arises from significant uncertainty and variability occurring at small time scales associated with increased penetration of renewables. Specifically, the problem is with ensuring economic and efficient utilization of DERs, while also meeting operational objectives such as adequate frequency performance. One possible solution is to reduce the time step at which tertiary controls are implemented and to ensure feedback and look-ahead capability are incorporated tomore » handle variability and uncertainty. However, reducing the time step of tertiary controls necessitates investigating time-scale coupling with primary controls so as not to exacerbate system stability issues. In this paper, an optimal coordination (OC) strategy, which considers multiple time-scales, is proposed for isolated microgrid systems with a mix of DERs. This coordination strategy is based on an online moving horizon optimization approach. The effectiveness of the strategy was evaluated in terms of economics, technical performance, and computation time by varying key parameters that significantly impact performance. The illustrative example with realistic scenarios on a simulated isolated microgrid test system suggests that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems.« less

Terrestrial Waters and Sea Level Variations on Interannual Time Scale

NASA Technical Reports Server (NTRS)

Llovel, W.; Becker, M.; Cazenave, A.; Jevrejeva, S.; Alkama, R.; Decharme, B.; Douville, H.; Ablain, M.; Beckley, B.

2011-01-01

On decadal to multi-decadal time scales, thermal expansion of sea waters and land ice loss are the main contributors to sea level variations. However, modification of the terrestrial water cycle due to climate variability and direct anthropogenic forcing may also affect sea level. For the past decades, variations in land water storage and corresponding effects on sea level cannot be directly estimated from observations because these are almost non-existent at global continental scale. However, global hydrological models developed for atmospheric and climatic studies can be used for estimating total water storage. For the recent years (since mid-2002), terrestrial water storage change can be directly estimated from observations of the GRACE space gravimetry mission. In this study, we analyse the interannual variability of total land water storage, and investigate its contribution to mean sea level variability at interannual time scale. We consider three different periods that, each, depend on data availability: (1) GRACE era (2003-2009), (2) 1993-2003 and (3) 1955-1995. For the GRACE era (period 1), change in land water storage is estimated using different GRACE products over the 33 largest river basins worldwide. For periods 2 and 3, we use outputs from the ISBA-TRIP (Interactions between Soil, Biosphere, and Atmosphere-Total Runoff Integrating Pathways) global hydrological model. For each time span, we compare change in land water storage (expressed in sea level equivalent) to observed mean sea level, either from satellite altimetry (periods 1 and 2) or tide gauge records (period 3). For each data set and each time span, a trend has been removed as we focus on the interannual variability. We show that whatever the period considered, interannual variability of the mean sea level is essentially explained by interannual fluctuations in land water storage, with the largest contributions arising from tropical river basins.

Multi-scale responses of scattering layers to environmental variability in Monterey Bay, California

NASA Astrophysics Data System (ADS)

Urmy, Samuel S.; Horne, John K.

2016-07-01

A 38 kHz upward-facing echosounder was deployed on the seafloor at a depth of 875 m in Monterey Bay, CA, USA (36° 42.748‧N, 122° 11.214‧W) from 27 February 2009 to 18 August 2010. This 18-month record of acoustic backscatter was compared to oceanographic time series from a nearby data buoy to investigate the responses of animals in sound-scattering layers to oceanic variability at seasonal and sub-seasonal time scales. Pelagic animals, as measured by acoustic backscatter, moved higher in the water column and decreased in abundance during spring upwelling, attributed to avoidance of a shoaling oxycline and advection offshore. Seasonal changes were most evident in a non-migrating scattering layer near 500 m depth that disappeared in spring and reappeared in summer, building to a seasonal maximum in fall. At sub-seasonal time scales, similar responses were observed after individual upwelling events, though they were much weaker than the seasonal relationship. Correlations of acoustic backscatter with oceanographic variability also differed with depth. Backscatter in the upper water column decreased immediately following upwelling, then increased approximately 20 days later. Similar correlations existed deeper in the water column, but at increasing lags, suggesting that near-surface productivity propagated down the water column at 10-15 m d-1, consistent with sinking speeds of marine snow measured in Monterey Bay. Sub-seasonal variability in backscatter was best correlated with sea-surface height, suggesting that passive physical transport was most important at these time scales.

A comment on the use of flushing time, residence time, and age as transport time scales

USGS Publications Warehouse

Monsen, N.E.; Cloern, J.E.; Lucas, L.V.; Monismith, Stephen G.

2002-01-01

Applications of transport time scales are pervasive in biological, hydrologic, and geochemical studies yet these times scales are not consistently defined and applied with rigor in the literature. We compare three transport time scales (flushing time, age, and residence time) commonly used to measure the retention of water or scalar quantities transported with water. We identify the underlying assumptions associated with each time scale, describe procedures for computing these time scales in idealized cases, and identify pitfalls when real-world systems deviate from these idealizations. We then apply the time scale definitions to a shallow 378 ha tidal lake to illustrate how deviations between real water bodies and the idealized examples can result from: (1) non-steady flow; (2) spatial variability in bathymetry, circulation, and transport time scales; and (3) tides that introduce complexities not accounted for in the idealized cases. These examples illustrate that no single transport time scale is valid for all time periods, locations, and constituents, and no one time scale describes all transport processes. We encourage aquatic scientists to rigorously define the transport time scale when it is applied, identify the underlying assumptions in the application of that concept, and ask if those assumptions are valid in the application of that approach for computing transport time scales in real systems.

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Spatiotemporal variability of stream habitat and movement of three species of fish

USGS Publications Warehouse

Roberts, J.H.; Angermeier, P.L.

2007-01-01

Relationships between environmental variability and movement are poorly understood, due to both their complexity and the limited ecological scope of most movement studies. We studied movements of fantail (Etheostoma flabellare), riverweed (E. podostemone), and Roanoke darters (Percina roanoka) through two stream systems during two summers. We then related movement to variability in measured habitat attributes using logistic regression and exploratory data plots. We indexed habitat conditions at both microhabitat (i.e., patches of uniform depth, velocity, and substrate) and mesohabitat (i.e., riffle and pool channel units) spatial scales, and determined how local habitat conditions were affected by landscape spatial (i.e., longitudinal position, land use) and temporal contexts. Most spatial variability in habitat conditions and fish movement was unexplained by a site's location on the landscape. Exceptions were microhabitat diversity, which was greater in the less-disturbed watershed, and riffle isolation and predator density in pools, which were greater at more-downstream sites. Habitat conditions and movement also exhibited only minor temporal variability, but the relative influences of habitat attributes on movement were quite variable over time. During the first year, movements of fantail and riverweed darters were triggered predominantly by loss of shallow microhabitats; whereas, during the second year, microhabitat diversity was more strongly related (though in opposite directions) to movement of these two species. Roanoke darters did not move in response to microhabitat-scale variables, presumably because of the species' preference for deeper microhabitats that changed little over time. Conversely, movement of all species appeared to be constrained by riffle isolation and predator density in pools, two mesohabitat-scale attributes. Relationships between environmental variability and movement depended on both the spatiotemporal scale of consideration and the ecology of the species. Future studies that integrate across scales, taxa, and life-histories are likely to provide greater insight into movement ecology than will traditional, single-season, single-species approaches. ?? 2006 Springer-Verlag.

Do GCM's predict the climate.... Or the low frequency weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Schertzer, D.; Varon, D.

2012-04-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Characterization of large-scale fluctuations and short-term variability of Seine river daily streamflow (France) over the period 1950-2008 by empirical mode decomposition and the Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Massei, N.; Fournier, M.

2010-12-01

Daily Seine river flow from 1950 to 2008 was analyzed using Hilbert-Huang Tranform (HHT). For the last ten years, this method which combines the so-called Empirical Mode Decomposition (EMD) multiresolution analysis and the Hilbert transform has proven its efficiency for the analysis of transient oscillatory signals, although the mathematical definition of the EMD is not totally established yet. HHT also provides an interesting alternative to other time-frequency or time-scale analysis of non-stationary signals, the most famous of which being wavelet-based approaches. In this application of HHT to the analysis of the hydrological variability of the Seine river, we seek to characterize the interannual patterns of daily flow, differenciate them from the short-term dynamics and eventually interpret them in the context of regional climate regime fluctuations. In this aim, HHT is also applied to the North-Atlantic Oscillation (NAO) through the annual winter-months NAO index time series. For both hydrological and climatic signals, dominant variability scales are extracted and their temporal variations analyzed by determination of the intantaneous frequency of each component. When compared to previous ones obtained from continuous wavelet transform (CWT) on the same data, HHT results highlighted the same scales and somewhat the same internal components for each signal. However, HHT allowed the identification and extraction of much more similar features during the 1950-2008 period (e.g., around 7-yr, between NAO and Seine flow than what was obtained from CWT, which comes to say that variability scales in flow likely to originate from climatic regime fluctuations were much properly identified in river flow. In addition, a more accurate determination of singularities in the natural processes analyzed were authorized by HHT compared to CWT, in which case the time-frequency resolution partly depends on the basic properties of the filter (i.e., the reference wavelet chosen initially). Compared to CWT or even to discrete wavelet multiresolution analysis, HHT is auto-adaptive, non-parametric, allows an orthogonal decomposition of the signal analyzed and provides a more accurate estimation of changing variability scales across time for highly transient signals.

Variability and mass loss in IA O-B-A supergiants

NASA Technical Reports Server (NTRS)

Schild, R. E.; Garrison, R. F.; Hiltner, W. A.

1983-01-01

Recently completed catalogs of MK spectral types and UBV photometry of 1227 OB stars in the southern Milky Way have been analyzed to investigate brightness and color variability among the Ia supergiants. It is found that brightness variability is common among the O9-B1 supergiants with typical amplitudes about 0.1 and time scales longer than a week and shorter than 1000 days. Among the A supergiants fluctuations in U-B color are found on similar time scales and with amplitude about 0.1. For many early Ia supergiants there is a poor correlation between Balmer jump and spectral type, as had been known previously. An attempt to correlate the Balmer jump deficiency with mass loss rate yielded uncertain results.

Monthly means of selected climate variables for 1985 - 1989

NASA Technical Reports Server (NTRS)

Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

1992-01-01

Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

Rapid variability, dying pulse trains and black holes

NASA Technical Reports Server (NTRS)

Stoeger, W. R.

1980-01-01

After reviewing the general model and arguments by which rapid temporal variability and quasi-periodicities are considered indicative of a compact source's possible black hole character, the paper presents a scenario for 'dying pulse trains'. These originate inside the inner edge of accretion disks encircling black holes from accreting flares or other self-luminous entities executing their final few revolutions before reaching the event horizon. Confirmed detection of such phenomena with time scales in the range 0.01 (M/solar mass) to 0.5 (M/solar mass)ms, where M is the mass of the compact source, would provide much better support for its black hole candidacy. Variability on time-scales larger than this by itself places few constraints on the nature of the compact object.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

NASA Astrophysics Data System (ADS)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (H<0: fluctuations decreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the anomaly variance. These scaling hindcasts have comparable - or smaller - RMS errors than existing GCM's. We discuss how these be further improved by going beyond time series forecasts to space-time.

Correlation Scales of the Turbulent Cascade at 1 au

NASA Astrophysics Data System (ADS)

Smith, Charles W.; Vasquez, Bernard J.; Coburn, Jesse T.; Forman, Miriam A.; Stawarz, Julia E.

2018-05-01

We examine correlation functions of the mixed, third-order expressions that, when ensemble-averaged, describe the cascade of energy in the inertial range of magnetohydrodynamic turbulence. Unlike the correlation function of primitive variables such as the magnetic field, solar wind velocity, temperature, and density, the third-order expressions decorrelate at a scale that is approximately 20% of the lag. This suggests the nonlinear dynamics decorrelate in less than one wavelength. Therefore, each scale can behave differently from one wavelength to the next. In the same manner, different scales within the inertial range can behave independently at any given time or location. With such a cascade that can be strongly patchy and highly variable, it is often possible to obtain negative cascade rates for short periods of time, as reported earlier for individual samples of data.

Long-Term and Rapid Radio Variability of the Blazar 3C 454.3 in 2010-2017

NASA Astrophysics Data System (ADS)

Gorshkov, A. G.; Ipatov, A. V.; Ipatova, I. A.; Konnikova, V. K.; Mardyshkin, V. V.; Mingaliev, M. G.; Kharinov, M. A.

2018-03-01

The article presents the results of observations of the blazar 3C 454.3 (J2253+1608), obtained in 2010-2017 on the RATAN-600 radio telescope of the Special Astrophysical Observatory at 4.6, 8.2, 11.2, and 21.7 GHz and on the 32-m Zelenchuk and Badary radio telescopes of the Quasar VLBI Network of the Institute of Applied Astronomy at 4.84 and 8.57 GHz. Long-term variability of the radio emission is studied, as well as variability on time scales of several days and intraday variability (IDV). Two flares were observed in the long-term light curve, in 2010 and in 2015-2017. The flux density at 21.7 GHz increased by a factor of ten during these flares. The delay in the maximum of the first flare at 4.85 GHz relative to the maximum at 21.7 GHz was six months. The time scale for variability on the descending branch of the first flare at 21.7 GHz was τvar = 1.2 yrs, yielding an upper limit on the linear size of the emitting region of 0.4 pc, corresponding to an angular size of 0.06 mas. The brightness temperature during the flare exceeded the Compton limit, implying a Doppler factor δ = 3.5, consistent with the known presence of a relativistic jet oriented close to the line of sight. No significant variability on time scales from several days to several weeks was found in five sets of daily observations carried out over 120 days. IDV was detected at 8.57 GHz on the 32-m telescopes in 30 of 61 successful observing sessions, with the presence of IDV correlated with the maxima of flares. The characteristic time scale for the IDV was from two to ten hours. A number of IDV light curves show the presence of a time delay in the maxima in the light curves for simultaneous observations carried out on the Badary and Zelenchuk antennas, which are widely separated in longitude. This demonstrates that the IDV most like arises in the interstellar medium.

Self-similarity in incompressible Navier-Stokes equations.

PubMed

Ercan, Ali; Kavvas, M Levent

2015-12-01

The self-similarity conditions of the 3-dimensional (3D) incompressible Navier-Stokes equations are obtained by utilizing one-parameter Lie group of point scaling transformations. It is found that the scaling exponents of length dimensions in i = 1, 2, 3 coordinates in 3-dimensions are not arbitrary but equal for the self-similarity of 3D incompressible Navier-Stokes equations. It is also shown that the self-similarity in this particular flow process can be achieved in different time and space scales when the viscosity of the fluid is also scaled in addition to other flow variables. In other words, the self-similarity of Navier-Stokes equations is achievable under different fluid environments in the same or different gravity conditions. Self-similarity criteria due to initial and boundary conditions are also presented. Utilizing the proposed self-similarity conditions of the 3D hydrodynamic flow process, the value of a flow variable at a specified time and space can be scaled to a corresponding value in a self-similar domain at the corresponding time and space.

Effects of the 7-8-year cycle in daily mean air temperature as a cross-scale information transfer

NASA Astrophysics Data System (ADS)

Jajcay, Nikola; Hlinka, Jaroslav; Paluš, Milan

2015-04-01

Using a novel nonlinear time-series analysis method, an information transfer from larger to smaller scales of the air temperature variability has been observed in daily mean surface air temperature (SAT) data from European stations as the influence of the phase of slow oscillatory phenomena with periods around 6-11 years on amplitudes of the variability characterized by smaller temporal scales from a few months to 4-5 years [1]. The strongest effect is exerted by an oscillatory mode with the period close to 8 years and its influence can be seen in 1-2 °C differences of the conditional SAT means taken conditionally on the phase of the 8-year cycle. The size of this effect, however, changes in space and time. The changes in time are studied using sliding window technique, showing that the effect evolves in time, and during the last decades the effect is stronger and significant. Sliding window technique was used along with seasonal division of the data, and it has been found that the cycle is most pronounced in the winter season. Different types of surrogate data are applied in order to establish statistical significance and distinguish the effect of the 7-8-yr cycle from climate variability on shorter time scales. [1] M. Palus, Phys. Rev. Lett. 112 078702 (2014) This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001.

The East Asian Jet Stream and Asian-Pacific-American Climate

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

2000-01-01

The upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region during winter. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet stream is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation especially over East Asia. The variabilities of the EAJ on these time scales have been relatively well documented. It has also been understood since decades ago that the interannual. variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation. However, many questions remain for the year-to-year variabilities of the EAJ and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the EAJ and ENSO play different roles in modulating the APA climate? How is the jet stream linked to the non-ENSO-related sea surface temperature (SST) anomalies and to the Pacific/North American (PNA) teleconnection pattern?

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach basically consisted in 1- decomposing both signals (SLP field and precipitation or streamflow) using discrete wavelet multiresolution analysis and synthesis, 2- generating one statistical downscaling model per time-scale, 3- summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD ; in addition, the scale-dependent spatial patterns associated to the model matched quite well those obtained from scale-dependent composite analysis. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either prepciptation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with flood and extremely low-flow/drought periods (e.g., winter 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. Further investigations would be required to address the issue of the stationarity of the large-scale/local-scale relationships and to test the capability of the multiresolution ESD model for interannual-to-interdecadal forecasting. In terms of methodological approach, further investigations may concern a fully comprehensive sensitivity analysis of the modeling to the parameter of the multiresolution approach (different families of scaling and wavelet functions used, number of coefficients/degree of smoothness, etc.).

Seemingly unrelated intervention time series models for effectiveness evaluation of large scale environmental remediation.

PubMed

Ip, Ryan H L; Li, W K; Leung, Kenneth M Y

2013-09-15

Large scale environmental remediation projects applied to sea water always involve large amount of capital investments. Rigorous effectiveness evaluations of such projects are, therefore, necessary and essential for policy review and future planning. This study aims at investigating effectiveness of environmental remediation using three different Seemingly Unrelated Regression (SUR) time series models with intervention effects, including Model (1) assuming no correlation within and across variables, Model (2) assuming no correlation across variable but allowing correlations within variable across different sites, and Model (3) allowing all possible correlations among variables (i.e., an unrestricted model). The results suggested that the unrestricted SUR model is the most reliable one, consistently having smallest variations of the estimated model parameters. We discussed our results with reference to marine water quality management in Hong Kong while bringing managerial issues into consideration. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of Hydrologic and Meteorological Impacts on Dengue Fever Incidences in Southern Taiwan using Time- Frequency Method

NASA Astrophysics Data System (ADS)

Tsai, Christina; Yeh, Ting-Gu

2017-04-01

Extreme weather events are occurring more frequently as a result of climate change. Recently dengue fever has become a serious issue in southern Taiwan. It may have characteristic temporal scales that can be identified. Some researchers have hypothesized that dengue fever incidences are related to climate change. This study applies time-frequency analysis to time series data concerning dengue fever and hydrologic and meteorological variables. Results of three time-frequency analytical methods - the Hilbert Huang transform (HHT), the Wavelet Transform (WT) and the Short Time Fourier Transform (STFT) are compared and discussed. A more effective time-frequency analysis method will be identified to analyze relevant time series data. The most influential time scales of hydrologic and meteorological variables that are associated with dengue fever are determined. Finally, the linkage between hydrologic/meteorological factors and dengue fever incidences can be established.

Optimal variable-grid finite-difference modeling for porous media

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yin, Xingyao; Li, Haishan

2014-12-01

Numerical modeling of poroelastic waves by the finite-difference (FD) method is more expensive than that of acoustic or elastic waves. To improve the accuracy and computational efficiency of seismic modeling, variable-grid FD methods have been developed. In this paper, we derived optimal staggered-grid finite difference schemes with variable grid-spacing and time-step for seismic modeling in porous media. FD operators with small grid-spacing and time-step are adopted for low-velocity or small-scale geological bodies, while FD operators with big grid-spacing and time-step are adopted for high-velocity or large-scale regions. The dispersion relations of FD schemes were derived based on the plane wave theory, then the FD coefficients were obtained using the Taylor expansion. Dispersion analysis and modeling results demonstrated that the proposed method has higher accuracy with lower computational cost for poroelastic wave simulation in heterogeneous reservoirs.

Synaptic dynamics contribute to long-term single neuron response fluctuations.

PubMed

Reinartz, Sebastian; Biro, Istvan; Gal, Asaf; Giugliano, Michele; Marom, Shimon

2014-01-01

Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses-activated in response to a given stimulus-on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.

Investigating precipitation changes of anthropic origin: data and methodological issues

NASA Astrophysics Data System (ADS)

de Lima, Isabel; Lovejoy, Shaun

2017-04-01

There is much concern about the social, environmental and economic impacts of climate change that could result directly from changes in temperature and precipitation. For temperature, the situation is better understood; but despite the many studies that have been already dedicated to precipitation, change in this process - that could be associated to the transition to the Anthropocene - has not yet been convincingly proven. A large fraction of those studies have been exploring temporal (linear) trends in local precipitation, sometimes using records over only a few decades; other fewer studies have been dedicated to investigating global precipitation change. Overall, precipitation change of anthropic origin has showed to be difficult to establish with high statistical significance and, moreover, different data and products have displayed important discrepancies; this is valid even for global precipitation. We argue that the inadequate resolution and length of the data commonly used, as well as methodological issues, are among the main factors limiting the ability to identify the signature of change in precipitation. We propose several ways in which one can hope to improve the situation - or at least - clarify the difficulties. From the point of view of statistical analysis, the problem is one of detecting a low frequency anthropogenic signal in the presence of "noise" - the natural variability (the latter includes both internal dynamics and responses to volcanic, solar or other natural forcings). A consequence is that as one moves to longer and longer time scales, fluctuations are increasingly averaged and at some point, the anthropogenic signal will stand out above the natural variability noise. This approach can be systematized using scaling fluctuation analysis to characterizing different precipitation scaling regimes: weather, macroweather, climate - from higher to lower frequencies; in the anthropocene, the macroweather regime covers the range of time scales from about a month to ≈30 years. We illustrate this using local gauge data and three qualitatively different global scale precipitation products (from gauges, reanalyses and a satellite and gauge hybrid) that allow to investigate precipitation from monthly to centennial scales and in space from planetary down to 5°x5° scales. By systematically characterizing precipitation variability across wide ranges of time and space scales, we show that the anthropogenic signal only exceeded the natural variability at time scales larger than ≈20 years, so that the disagreement in the trends can be traced to these low frequencies.

Forced and intrinsic variability in the response to increased wind stress of an idealized Southern Ocean

NASA Astrophysics Data System (ADS)

Wilson, Chris; Hughes, Chris W.; Blundell, Jeffrey R.

2015-01-01

use ensemble runs of a three layer, quasi-geostrophic idealized Southern Ocean model to explore the roles of forced and intrinsic variability in response to a linear increase of wind stress imposed over a 30 year period. We find no increase of eastward circumpolar volume transport in response to the increased wind stress. A large part of the resulting time series can be explained by a response in which the eddy kinetic energy is linearly proportional to the wind stress with a possible time lag, but no statistically significant lag is found. However, this simple relationship is not the whole story: several intrinsic time scales also influence the response. We find an e-folding time scale for growth of small perturbations of 1-2 weeks. The energy budget for intrinsic variability at periods shorter than a year is dominated by exchange between kinetic and potential energy. At longer time scales, we find an intrinsic mode with period in the region of 15 years, which is dominated by changes in potential energy and frictional dissipation in a manner consistent with that seen by Hogg and Blundell (2006). A similar mode influences the response to changing wind stress. This influence, robust to perturbations, is different from the supposed linear relationship between wind stress and eddy kinetic energy, and persists for 5-10 years in this model, suggestive of a forced oscillatory mode with period of around 15 years. If present in the real ocean, such a mode would imply a degree of predictability of Southern Ocean dynamics on multiyear time scales.

Wind-driven variations in an overturning circulation

NASA Astrophysics Data System (ADS)

Bringedal, Carina; Eldevik, Tor; Spall, Michael

2017-04-01

The Atlantic overturning circulation and poleward heat transport is balanced by northern heat loss to the atmosphere and corresponding water mass transformation. The structure of this circulation and transformation is particularly manifested - and observed - at the Greenland-Scotland ridge. There is however a rich variability in the exchanges across the ridge on seasonal and yearly time scales. This variability has been almost perfectly captured in atmospherically forced ocean GCMs (e.g. Olsen et al 2008, Sandø et al 2012), suggesting that on shorter time scales the variability of the exchanges are connected to sea level pressure and corresponding wind stress forcing. Focusing on seasonal and yearly time scales, we accordingly propose that the connection between the exchanges of overturning waters across the Greenland-Scotland ridge and the sea level pressure must be direct and simple, and we use idealized simulations to support this hypothesis. The mechanisms underlying the connection are formulated through conceptual models. Although the models and simulations are simplified with respect to bathymetry and hydrography, they can reproduce the main features of the overturning circulation in the Nordic seas. In the observations, the variable exchanges can largely be related to sea level pressure variations and large scale wind patterns, and the idealized simulations and accompanying conceptual models show how these impacts can manifest via coastal downwelling and gyre circulation. S. M. Olsen, B. Hansen, D. Quadfasel and S. Østerhus, Observed and modelled stability of overflow across the Greenland-Scotland ridge, Nature 455, (2008) A. B. Sandø, J. E. Ø. Nilsen, T. Eldevik and M. Bentsen, Mechanisms for variable North Atlantic-Nordic seas exchanges, Journal of Geophysical Research 117, (2012)

Thermal maps of Jupiter - Spatial organization and time dependence of stratospheric temperatures, 1980 to 1990

NASA Technical Reports Server (NTRS)

Orton, Glenn S.; Friedson, A. James; Baines, Kevin H.; Martin, Terry Z.; West, Robert A.; Caldwell, John; Hammel, Heidi B.; Bergstralh, Jay T.; Malcolm, Michael E.

1991-01-01

The spatial organization and time dependence of Jupiter's stratospheric temperatures have been measured by observing thermal emission from the 7.8-micrometer CH4 band. These temperatures, observed through the greater part of a Jovian year, exhibit the influence of seasonal radiative forcing. Distinct bands of high temperature are located at the poles and midlatitudes, while the equator alternates between warm and cold with a period of approximately 4 years. Substantial longitudinal variability is often observed within the warm midlatitude bands, and occasionally elsewhere on the planet. This variability includes small, localized structures, as well as large-scale waves with wavelengths longer than about 30,000 kilometers. The amplitudes of the waves vary on a time scale of about 1 month; structures on a smaller scale may have lifetimes of only days. Waves observed in 1985, 1987, and 1988 propagated with group velocities less than + or - 30 meters/sec.

Response to Comment on "Does the Earth Have an Adaptive Infrared IRIS?"

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.

2001-01-01

Harrison's (2001) Comment on the Methodology in Lindzen et al (2001) has prompted re-examination of several aspects of study. Probably the most significant disagreement in our conclusions is due to our different approaches to minimizing the influence of long-time-scale variations in the variables A and T on the results. Given the strength of the annual cycle and the 20-month period covered by the data, we believe that removing monthly means is a better approach to minimizing the long-time-scale behavior of the data than removal of the linear trend, which might actually add spurious long- time- scale variability into the modified data. We have also indicated how our statistical methods of establishing statistical significance differ. More definitive conclusions may only possible after more data have been analyzed, but we feel that our results are robust enough to encourage further study of this phenomenon.

Use of color maps and wavelet coherence to discern seasonal and interannual climate influences on streamflow variability in northern catchments

NASA Astrophysics Data System (ADS)

Carey, Sean K.; Tetzlaff, Doerthe; Buttle, Jim; Laudon, Hjalmar; McDonnell, Jeff; McGuire, Kevin; Seibert, Jan; Soulsby, Chris; Shanley, Jamie

2013-10-01

The higher midlatitudes of the northern hemisphere are particularly sensitive to change due to the important role the 0°C isotherm plays in the phase of precipitation and intermediate storage as snow. An international intercatchment comparison program called North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. Here eight North-Watch catchments located in Sweden (Krycklan), Scotland (Girnock and Strontian), the United States (Sleepers River, Hubbard Brook, and HJ Andrews), and Canada (Dorset and Wolf Creek) with 10 continuous years of daily precipitation and runoff data were selected to assess daily to seasonal coupling of precipitation (P) and runoff (Q) using wavelet coherency, and to explore the patterns and scales of variability in streamflow using color maps. Wavelet coherency revealed that P and Q were decoupled in catchments with cold winters, yet were strongly coupled during and immediately following the spring snowmelt freshet. In all catchments, coupling at shorter time scales occurred during wet periods when the catchment was responsive and storage deficits were small. At longer time scales, coupling reflected coherence between seasonal cycles, being enhanced at sites with enhanced seasonality in P. Color maps were applied as an alternative method to identify patterns and scales of flow variability. Seasonal versus transient flow variability was identified along with the persistence of that variability on influencing the flow regime. While exploratory in nature, this intercomparison exercise highlights the importance of climate and the 0°C isotherm on the functioning of northern catchments.

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

PubMed

Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

2011-07-01

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.

Long-term forecasting of internet backbone traffic.

PubMed

Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

2005-09-01

We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

Decadal climate variability and the spatial organization of deep hydrological drought

NASA Astrophysics Data System (ADS)

Barros, Ana P.; Hodes, Jared L.; Arulraj, Malarvizhi

2017-10-01

Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (< 6 years) space-time modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

Classification of Hot Stars by Disk Variability using Hα Line Emission Characteristics

NASA Astrophysics Data System (ADS)

Hoyt Hannah, Christian; Glennon Fagan, W.; Tycner, Christopher

2018-06-01

The variability associated with circumstellar disks around hot and massive stars has been observed on time scales ranging from less than a day to decades. Variations detected in line emission from circumstellar disks on long time scales are typically attributed to disk-growth and disk-loss events. However, in order to fully describe and model such phenomena, adequate spectroscopic observations over long time scales are needed. In this project, we conduct a comprehensive study that is based on spectra recorded over a 14-year period (2005 to 2018) of roughly 100 B-type stars. Using results from a representative sample of over 20 targets, we illustrate how the Hα emission line, one of the most prominent emission features from circumstellar disks, can be used to monitor the variability associated with these systems. Using high-resolution spectra, we utilize line emission characteristics such as equivalent width, peak strength(s), and line-width to setup a classification scheme that describes different types of variabilities. This in turn can be used to divide the systems in disk-growth, disk-loss, variable and stable categories. With additional numerical disk modeling, the recorded variations based on emission line characteristics can also be used to describe changes in disk temperature and density structure. The aim is to develop a tool to help further our understanding of the processes behind the production and eventual dissipation of the circumstellar disks found in hot stars. This work has been supported by NSF grant AST-1614983.

Microlensing makes lensed quasar time delays significantly time variable

NASA Astrophysics Data System (ADS)

Tie, S. S.; Kochanek, C. S.

2018-01-01

The time delays of gravitationally lensed quasars are generally believed to be unique numbers whose measurement is limited only by the quality of the light curves and the models for the contaminating contribution of gravitational microlensing to the light curves. This belief is incorrect - gravitational microlensing also produces changes in the actual time delays on the ∼day(s) light-crossing time-scale of the emission region. This is due to a combination of the inclination of the disc relative to the line of sight and the differential magnification of the temperature fluctuations producing the variability. We demonstrate this both mathematically and with direct calculations using microlensing magnification patterns. Measuring these delay fluctuations can provide a physical scale for microlensing observations, removing the need for priors on either the microlens masses or the component velocities. That time delays in lensed quasars are themselves time variable likely explains why repeated delay measurements of individual lensed quasars appear to vary by more than their estimated uncertainties. This effect is also a new important systematic problem for attempts to use time delays in lensed quasars for cosmology or to detect substructures (satellites) in lens galaxies.

Flexible and scalable methods for quantifying stochastic variability in the era of massive time-domain astronomical data sets

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

Kelly, Brandon C.; Becker, Andrew C.; Sobolewska, Malgosia

2014-06-10

We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placingmore » them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.« less

A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

NASA Astrophysics Data System (ADS)

Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

2018-01-01

Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

Nonlinear Time Series Analysis in the Absence of Strong Harmonics

NASA Astrophysics Data System (ADS)

Stine, Peter; Jevtic, N.

2010-05-01

Nonlinear time series analysis has successfully been used for noise reduction and for identifying long term periodicities in variable star light curves. It was thought that good noise reduction could be obtained when a strong fundamental and second harmonic are present. We show that, quite unexpectedly, this methodology for noise reduction can be efficient for data with very noisy power spectra without a strong fundamental and second harmonic. Not only can one obtain almost two orders of magnitude noise reduction of the white noise tail, insight can also be gained into the short time scale of organized behavior. Thus, we are able to obtain an estimate of this short time scale, which is on the order of 1.5 hours in the case of a variable white dwarf.

Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models

NASA Astrophysics Data System (ADS)

Schneider, Adam; Flanner, Mark; Perket, Justin

2018-02-01

Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.

Impacts of short-time scale water column variability on broadband high-frequency acoustic wave propagation

NASA Astrophysics Data System (ADS)

Eickmeier, Justin

Acoustical oceanography is one way to study the ocean, its internal layers, boundaries and all processes occurring within using underwater acoustics. Acoustical sensing techniques allows for the measurement of ocean processes from within that logistically or financially preclude traditional in-situ measurements. Acoustic signals propagate as pressure wavefronts from a source to a receiver through an ocean medium with variable physical parameters. The water column physical parameters that change acoustic wave propagation in the ocean include temperature, salinity, current, surface roughness, seafloor bathymetry, and vertical stratification over variable time scales. The impacts of short-time scale water column variability on acoustic wave propagation include coherent and incoherent surface reflections, wavefront arrival time delay, focusing or defocusing of the intensity of acoustic beams and refraction of acoustic rays. This study focuses on high-frequency broadband acoustic waves, and examines the influence of short-time scale water column variability on broadband high-frequency acoustics, wavefronts, from 7 to 28 kHz, in shallow water. Short-time scale variability is on the order of seconds to hours and the short-spatial scale variability is on the order of few centimeters. Experimental results were collected during an acoustic experiment along 100 m isobaths and data analysis was conducted using available acoustic wave propagation models. Three main topics are studied to show that acoustic waves are viable as a remote sensing tool to measure oceanographic parameters in shallow water. First, coherent surface reflections forming striation patterns, from multipath receptions, through rough surface interaction of broadband acoustic signals with the dynamic sea surface are analyzed. Matched filtered results of received acoustic waves are compared with a ray tracing numerical model using a sea surface boundary generated from measured water wave spectra at the time of signal propagation. It is determined that on a time scale of seconds, corresponding to typical periods of surface water waves, the arrival time of reflected acoustic signals from surface waves appear as striation patterns in measured data and can be accurately modelled by ray tracing. Second, changes in acoustic beam arrival angle and acoustic ray path influenced by isotherm depth oscillations are analyzed using an 8-element delay-sum beamformer. The results are compared with outputs from a two-dimensional (2-D) parabolic equation (PE) model using measured sound speed profiles (SSPs) in the water column. Using the method of beamforming on the received signal, the arrival time and angle of an acoustic beam was obtained for measured acoustic signals. It is determined that the acoustic ray path, acoustic beam intensity and angular spread are a function of vertical isotherm oscillations on a time scale of minutes and can be modeled accurately by a 2-D PE model. Third, a forward problem is introduced which uses acoustic wavefronts received on a vertical line array, 1.48 km from the source, in the lower part of the water column to infer range dependence or independence in the SSP. The matched filtering results of received acoustic wavefronts at all hydrophone depths are compared with a ray tracing routine augmented to calculate only direct path and bottom reflected signals. It is determined that the SSP range dependence can be inferred on a time scale of hours using an array of hydrophones spanning the water column. Sound speed profiles in the acoustic field were found to be range independent for 11 of the 23 hours in the measurements. A SSP cumulative reconstruction process, conducted from the seafloor to the sea surface, layer-by-layer, identifies critical segments in the SSP that define the ray path, arrival time and boundary interactions. Data-model comparison between matched filtered arrival time spread and arrival time output from the ray tracing was robust when the SSP measured at the receiver was input to the model. When the SSP measured nearest the source (at the same instant in time) was input to the ray tracing model, the data-model comparison was poor. It was determined that the cumulative sound speed change in the SSP near the source was 1.041 m/s greater than that of the SSP at the receiver and resulted in the poor data-model comparison. In this study, the influences on broadband acoustic wave propagation in the frequency range of 7 to 28 kHz of spatial and temporal changes in the oceanography of shallow water regions are addressed. Acoustic waves can be used as remote sensing tools to measure oceanographic parameters in shallow water and data-model comparison results show a direct relationship between the oceanographic variations and acoustic wave propagations.

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

PubMed Central

Bean, William T.; Stafford, Robert; Butterfield, H. Scott; Brashares, Justin S.

2014-01-01

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists. PMID:25237807

Scale and legacy controls on catchment nutrient export regimes

NASA Astrophysics Data System (ADS)

Howden, N. J. K.; Burt, T.; Worrall, F.

2017-12-01

Nutrient dynamics in river catchments are complex: water and chemical fluxes are highly variable in low-order streams, but this variability declines as fluxes move through higher-order reaches. This poses a major challenge for process understanding as much effort is focussed on long-term monitoring of the main river channel (a high-order reach), and therefore the data available to support process understanding are predominantly derived from sites where much of the transient response of nutrient export is masked by the effect of averaging over both space and time. This may be further exacerbated at all scales by the accumulation of legacy nutrient sources in soils, aquifers and pore waters, where historical activities have led to nutrient accumulation where the catchment system is transport limited. Therefore it is of particular interest to investigate how the variability of nutrient export changes both with catchment scale (from low to high-order catchment streams) and with the presence of legacy sources, such that the context of infrequent monitoring on high-order streams can be better understood. This is not only a question of characterising nutrient export regimes per se, but also developing a more thorough understanding of how the concepts of scale and legacy may modify the statistical characteristics of observed responses across scales in both space and time. In this paper, we use synthetic data series and develop a model approach to consider how space and timescales combine with impacts of legacy sources to influence observed variability in catchment export. We find that: increasing space and timescales tend to reduce the observed variance in nutrient exports, due to an increase in travel times and greater mixing, and therefore averaging, of sources; increasing the influence of legacy sources inflates the variance, with the level of inflation dictated by the residence time of the respective sources.

Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health risk

PubMed Central

Shaffer, Fred

2015-01-01

Heart rate variability, the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges. This article briefly reviews neural regulation of the heart and offers some new perspectives on mechanisms underlying the very low frequency rhythm of heart rate variability. Interpretation of heart rate variability rhythms in the context of health risk and physiological and psychological self-regulatory capacity assessment is discussed. The cardiovascular regulatory centers in the spinal cord and medulla integrate inputs from higher brain centers with afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. We also discuss the intrinsic cardiac nervous system and the heart-brain connection pathways, through which afferent information can influence activity in the subcortical, frontocortical, and motor cortex areas. In addition, the use of real-time HRV feedback to increase self-regulatory capacity is reviewed. We conclude that the heart's rhythms are characterized by both complexity and stability over longer time scales that reflect both physiological and psychological functional status of these internal self-regulatory systems. PMID:25694852

Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health risk.

PubMed

McCraty, Rollin; Shaffer, Fred

2015-01-01

Heart rate variability, the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges. This article briefly reviews neural regulation of the heart and offers some new perspectives on mechanisms underlying the very low frequency rhythm of heart rate variability. Interpretation of heart rate variability rhythms in the context of health risk and physiological and psychological self-regulatory capacity assessment is discussed. The cardiovascular regulatory centers in the spinal cord and medulla integrate inputs from higher brain centers with afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. We also discuss the intrinsic cardiac nervous system and the heart-brain connection pathways, through which afferent information can influence activity in the subcortical, frontocortical, and motor cortex areas. In addition, the use of real-time HRV feedback to increase self-regulatory capacity is reviewed. We conclude that the heart's rhythms are characterized by both complexity and stability over longer time scales that reflect both physiological and psychological functional status of these internal self-regulatory systems.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

White dwarf variability with gPhoton: pulsators

NASA Astrophysics Data System (ADS)

Tucker, Michael A.; Fleming, Scott W.; Pelisoli, Ingrid; Romero, Alejandra; Bell, Keaton J.; Kepler, S. O.; Caton, Daniel B.; Debes, John; Montgomery, Michael H.; Thompson, Susan E.; Koester, Detlev; Million, Chase; Shiao, Bernie

2018-04-01

We present results from a search for short time-scale white dwarf variability using gPhoton, a time-tagged data base of GALEX photon events and associated software package. We conducted a survey of 320 white dwarf stars in the McCook-Sion catalogue, inspecting each for photometric variability with particular emphasis on variability over time-scales less than ˜30 min. From that survey, we present the discovery of a new pulsating white dwarf: WD 2246-069. A Ca II K line is found in archival ESO spectra and an IR excess is seen in WISE W1 and W2 bands. Its independent modes are identified in follow-up optical photometry and used to model its interior structure. Additionally, we detect UV pulsations in four previously known pulsating ZZ Ceti-type (DAVs). Included in this group is the simultaneous fitting of the pulsations of WD 1401-147 in optical, near-ultraviolet and far-ultraviolet bands using nearly concurrent Whole Earth Telescope and GALEX data, providing observational insight into the wavelength dependence of white dwarf pulsation amplitudes.

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.Above results are discussed in a peer-review paper just being accepted for publication on Climate Dynamics (Alessandri et al., 2017; doi:10.1007/s00382-017-3766-y).

Time-resolved spectroscopyHiifill of the peculiar Hα variable Be star HD 76534

NASA Astrophysics Data System (ADS)

Oudmaijer, René D.; Drew, Janet E.

1999-10-01

We present time-resolved spectroscopy of the Be star HD 76534, which was observed to have an Hα outburst in 1995, when the line went from photospheric absorption to emission at a level of more than two times the continuum within 2.5 hours. To investigate the short-term behaviour of the spectrum of HD 76534 we have obtained 30 spectra within two hours real-time and searched for variations in the spectrum. Within the levels of statistical significance, no variability was found. Rather than periodic on short time scales, the Hα behaviour seems to be commonly episodic on longer (> 1 year) time scales, as an assessment of the existing data on the Hα line and the Hipparcos photometry suggests. HD 76534 underwent only 1 photometric outburst in the 3 year span that the star was monitored by the Hipparcos satellite.

Hilbert-Huang spectral analysis for characterizing the intrinsic time-scales of variability in decennial time-series of surface solar radiation

NASA Astrophysics Data System (ADS)

Bengulescu, Marc; Blanc, Philippe; Wald, Lucien

2016-04-01

An analysis of the variability of the surface solar irradiance (SSI) at different local time-scales is presented in this study. Since geophysical signals, such as long-term measurements of the SSI, are often produced by the non-linear interaction of deterministic physical processes that may also be under the influence of non-stationary external forcings, the Hilbert-Huang transform (HHT), an adaptive, noise-assisted, data-driven technique, is employed to extract locally - in time and in space - the embedded intrinsic scales at which a signal oscillates. The transform consists of two distinct steps. First, by means of the Empirical Mode Decomposition (EMD), the time-series is "de-constructed" into a finite number - often small - of zero-mean components that have distinct temporal scales of variability, termed hereinafter the Intrinsic Mode Functions (IMFs). The signal model of the components is an amplitude modulation - frequency modulation (AM - FM) one, and can also be thought of as an extension of a Fourier series having both time varying amplitude and frequency. Following the decomposition, Hilbert spectral analysis is then employed on the IMFs, yielding a time-frequency-energy representation that portrays changes in the spectral contents of the original data, with respect to time. As measurements of surface solar irradiance may possibly be contaminated by the manifestation of different type of stochastic processes (i.e. noise), the identification of real, physical processes from this background of random fluctuations is of interest. To this end, an adaptive background noise null hypothesis is assumed, based on the robust statistical properties of the EMD when applied to time-series of different classes of noise (e.g. white, red or fractional Gaussian). Since the algorithm acts as an efficient constant-Q dyadic, "wavelet-like", filter bank, the different noise inputs are decomposed into components having the same spectral shape, but that are translated to the next lower octave in the spectral domain. Thus, when the sampling step is increased, the spectral shape of IMFs cannot remain at its original position, due to the new lower Nyquist frequency, and is instead pushed toward the lower scaled frequency. Based on these features, the identification of potential signals within the data should become possible without any prior knowledge of the background noises. When applying the above outlined procedure to decennial time-series of surface solar irradiance, only the component that has an annual time-scale of variability is shown to have statistical properties that diverge from those of noise. Nevertheless, the noise-like components are not completely devoid of information, as it is found that their AM components have a non-null rank correlation coefficient with the annual mode, i.e. the background noise intensity seems to be modulated by the seasonal cycle. The findings have possible implications on the modelling and forecast of the surface solar irradiance, by discriminating its deterministic from its quasi-stochastic constituents, at distinct local time-scales.

Atmospheric circulation patterns associated to the variability of River Ammer floods: evidence from observed and proxy data

NASA Astrophysics Data System (ADS)

Rimbu, N.; Czymzik, M.; Ionita, M.; Lohmann, G.; Brauer, A.

2015-09-01

The relationship between the frequency of River Ammer floods (southern Germany) and atmospheric circulation variability is investigated based on observational Ammer discharge data back to 1926 and a flood layer time series from varved sediments of the downstream Lake Ammersee for the pre-instrumental period back to 1766. A composite analysis reveals that, at synoptic time scales, observed River Ammer floods are associated with enhanced moisture transport from the Atlantic Ocean and the Mediterranean towards the Ammer region, a pronounced trough over Western Europe as well as enhanced potential vorticity at upper levels. We argue that this synoptic scale configuration can trigger heavy precipitation and floods in the Ammer region. Interannual to multidecadal increases in flood frequency as recorded in the instrumental discharge record are associated to a wave-train pattern extending from the North Atlantic to western Asia with a prominent negative center over western Europe. A similar atmospheric circulation pattern is associated to increases in flood layer frequency in the Lake Ammersee sediment record during the pre-instrumental period. We argue that the complete flood layer time-series from Lake Ammersee sediments covering the last 5500 years, contains information about atmospheric circulation variability on inter-annual to millennial time-scales.

The scaling of population persistence with carrying capacity does not asymptote in populations of a fish experiencing extreme climate variability.

PubMed

White, Richard S A; Wintle, Brendan A; McHugh, Peter A; Booker, Douglas J; McIntosh, Angus R

2017-06-14

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. © 2017 The Author(s).

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

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.

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

PubMed Central

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

Factors Influencing the Sahelian Paradox at the Local Watershed Scale: Causal Inference Insights

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Groenke, A.; Larsen, L.

2017-12-01

While the existence of paradoxical rainfall-runoff and rainfall-groundwater correlations are well established in the West African Sahel, the hydrologic mechanisms involved are poorly understood. In pursuit of mechanistic explanations, we perform a causal inference analysis on hydrologic variables in three watersheds in Benin and Niger. Using an ensemble of techniques, we compute the strength of relationships between observational soil moisture, runoff, precipitation, and temperature data at seasonal and event timescales. Performing analysis over a range of time lags allows dominant time scales to emerge from the relationships between variables. By determining the time scales of hydrologic connectivity over vertical and lateral space, we show differences in the importance of overland and subsurface flow over the course of the rainy season and between watersheds. While previous work on the paradoxical hydrologic behavior in the Sahel focuses on surface processes and infiltration, our results point toward the importance of subsurface flow to rainfall-runoff relationships in these watersheds. The hypotheses generated from our ensemble approach suggest that subsequent explorations of mechanistic hydrologic processes in the region include subsurface flow. Further, this work highlights how an ensemble approach to causal analysis can reveal nuanced relationships between variables even in poorly understood hydrologic systems.

A multiple-time-scale turbulence model based on variable partitioning of turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1987-01-01

A multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method is presented. In the model, the effect of the ratio of the production rate to the dissipation rate on eddy viscosity is modeled by use of the multiple-time-scales and a variable partitioning of the turbulent kinetic energy spectrum. The concept of a variable partitioning of the turbulent kinetic energy spectrum and the rest of the model details are based on the previously reported algebraic stress turbulence model. Example problems considered include: a fully developed channel flow, a plane jet exhausting into a moving stream, a wall jet flow, and a weakly coupled wake-boundary layer interaction flow. The computational results compared favorably with those obtained by using the algebraic stress turbulence model as well as experimental data. The present turbulence model, as well as the algebraic stress turbulence model, yielded significantly improved computational results for the complex turbulent boundary layer flows, such as the wall jet flow and the wake boundary layer interaction flow, compared with available computational results obtained by using the standard kappa-epsilon turbulence model.

A multiple-time-scale turbulence model based on variable partitioning of the turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1989-01-01

A multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method is presented. In the model, the effect of the ratio of the production rate to the dissipation rate on eddy viscosity is modeled by use of the multiple-time-scales and a variable partitioning of the turbulent kinetic energy spectrum. The concept of a variable partitioning of the turbulent kinetic energy spectrum and the rest of the model details are based on the previously reported algebraic stress turbulence model. Example problems considered include: a fully developed channel flow, a plane jet exhausting into a moving stream, a wall jet flow, and a weakly coupled wake-boundary layer interaction flow. The computational results compared favorably with those obtained by using the algebraic stress turbulence model as well as experimental data. The present turbulence model, as well as the algebraic stress turbulence model, yielded significantly improved computational results for the complex turbulent boundary layer flows, such as the wall jet flow and the wake boundary layer interaction flow, compared with available computational results obtained by using the standard kappa-epsilon turbulence model.

Scale-dependent temporal variations in stream water geochemistry.

PubMed

Nagorski, Sonia A; Moore, Iohnnie N; McKinnon, Temple E; Smith, David B

2003-03-01

A year-long study of four western Montana streams (two impacted by mining and two "pristine") evaluated surface water geochemical dynamics on various time scales (monthly, daily, and bi-hourly). Monthly changes were dominated by snowmelt and precipitation dynamics. On the daily scale, post-rain surges in some solute and particulate concentrations were similar to those of early spring runoff flushing characteristics on the monthly scale. On the bi-hourly scale, we observed diel (diurnal-nocturnal) cycling for pH, dissolved oxygen, water temperature, dissolved inorganic carbon, total suspended sediment, and some total recoverable metals at some or all sites. A comparison of the cumulative geochemical variability within each of the temporal groups reveals that for many water quality parameters there were large overlaps of concentration ranges among groups. We found that short-term (daily and bi-hourly) variations of some geochemical parameters covered large proportions of the variations found on a much longer term (monthly) time scale. These results show the importance of nesting short-term studies within long-term geochemical study designs to separate signals of environmental change from natural variability.

Scale-dependent temporal variations in stream water geochemistry

USGS Publications Warehouse

Nagorski, S.A.; Moore, J.N.; McKinnon, Temple E.; Smith, D.B.

2003-01-01

A year-long study of four western Montana streams (two impacted by mining and two "pristine") evaluated surface water geochemical dynamics on various time scales (monthly, daily, and bi-hourly). Monthly changes were dominated by snowmelt and precipitation dynamics. On the daily scale, post-rain surges in some solute and particulate concentrations were similar to those of early spring runoff flushing characteristics on the monthly scale. On the bi-hourly scale, we observed diel (diurnal-nocturnal) cycling for pH, dissolved oxygen, water temperature, dissolved inorganic carbon, total suspended sediment, and some total recoverable metals at some or all sites. A comparison of the cumulative geochemical variability within each of the temporal groups reveals that for many water quality parameters there were large overlaps of concentration ranges among groups. We found that short-term (daily and bi-hourly) variations of some geochemical parameters covered large proportions of the variations found on a much longer term (monthly) time scale. These results show the importance of nesting short-term studies within long-term geochemical study designs to separate signals of environmental change from natural variability.

Vocal exploration is locally regulated during song learning

PubMed Central

Ravbar, Primoz; Parra, Lucas C.; Lipkind, Dina; Tchernichovski, Ofer

2012-01-01

Exploratory variability is essential for sensory-motor learning, but it is not known how and at what time scales it is regulated. We manipulated song learning in zebra finches to experimentally control the requirements for vocal exploration in different parts of their song. We first trained birds to perform a one-syllable song, and once they mastered it we added a new syllable to the song model. Remarkably, when practicing the modified song, birds rapidly alternated between high and low acoustic variability to confine vocal exploration to the newly added syllable. Further, even within syllables, acoustic variability changed independently across song elements that were only milliseconds apart. Analysis of the entire vocal output during learning revealed that the variability of each song element decreased as it approached the target, correlating with momentary local distance from the target and less so with the overall distance. We conclude that vocal error is computed locally in sub-syllabic time scales and that song elements can be learned and crystalized independently. Songbirds have dedicated brain circuitry for vocal babbling in the anterior forebrain pathway (AFP), which generates exploratory song patterns that drive premotor neurons at the song nucleus RA (robust nucleus of the arcopallium). We hypothesize that either AFP adjusts the gain of vocal exploration in fine time scales, or that the sensitivity of RA premotor neurons to AFP/HVC inputs varies across song elements. PMID:22399765

Spring onset variations and long-term trends from new hemispheric-scale products and remote sensing

NASA Astrophysics Data System (ADS)

Dye, D. G.; Li, X.; Ault, T.; Zurita-Milla, R.; Schwartz, M. D.

2015-12-01

Spring onset is commonly characterized by plant phenophase changes among a variety of biophysical transitions and has important implications for natural and man-managed ecosystems. Here, we present a new integrated analysis of variability in gridded Northern Hemisphere spring onset metrics. We developed a set of hemispheric temperature-based spring indices spanning 1920-2013. As these were derived solely from meteorological data, they are used as a benchmark for isolating the climate system's role in modulating spring "green up" estimated from the annual cycle of normalized difference vegetation index (NDVI). Spatial patterns of interannual variations, teleconnections, and long-term trends were also analyzed in all metrics. At mid-to-high latitudes, all indices exhibit larger variability at interannual to decadal time scales than at spatial scales of a few kilometers. Trends of spring onset vary across space and time. However, compared to long-term trend, interannual to decadal variability generally accounts for a larger portion of the total variance in spring onset timing. Therefore, spring onset trends identified from short existing records may be aliased by decadal climate variations due to their limited temporal depth, even when these records span the entire satellite era. Based on our findings, we also demonstrated that our indices have skill in representing ecosystem-level spring phenology and may have important implications in understanding relationships between phenology, atmosphere dynamics and climate variability.

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

DOE PAGES

St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

2015-04-02

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. However, how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer 'how far is far enough,' we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25–2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation lengthmore » $$\\xi $$ that falls at least as fast as $${{\\tau }^{-1}}$$ . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.« less

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

NASA Astrophysics Data System (ADS)

St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

2015-04-01

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. But how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer ‘how far is far enough,’ we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25-2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation length ξ that falls at least as fast as {{τ }-1} . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Scale size-dependent characteristics of the nightside aurora

NASA Astrophysics Data System (ADS)

Humberset, B. K.; Gjerloev, J. W.; Samara, M.; Michell, R. G.

2017-02-01

We have determined the spatiotemporal characteristics of the magnetosphere-ionosphere (M-I) coupling using auroral imaging. Observations at fixed positions for an extended period of time are provided by a ground-based all-sky imager measuring the 557.7 nm auroral emissions. We report on a single event of nightside aurora (˜22 magnetic local time) preceding a substorm onset. To determine the spatiotemporal characteristics, we perform an innovative analysis of an all-sky imager movie (19 min duration, images at 3.31 Hz) that combines a two-dimensional spatial fast Fourier transform with a temporal correlation. We find a scale size-dependent variability where the largest scale sizes are stable on timescales of minutes while the small scale sizes are more variable. When comparing two smaller time intervals of different types of auroral displays, we find a variation in their characteristics. The characteristics averaged over the event are in remarkable agreement with the spatiotemporal characteristics of the nightside field-aligned currents during moderately disturbed times. Thus, two different electrodynamical parameters of the M-I coupling show similar behavior. This gives independent support to the claim of a system behavior that uses repeatable solutions to transfer energy and momentum from the magnetosphere to the ionosphere.

Estimating Agricultural Nitrous Oxide Emissions

USDA-ARS?s Scientific Manuscript database

Nitrous oxide emissions are highly variable in space and time and different methodologies have not agreed closely, especially at small scales. However, as scale increases, so does the agreement between estimates based on soil surface measurements (bottom up approach) and estimates derived from chang...

Hierarchical coarse-graining model for photosystem II including electron and excitation-energy transfer processes.

PubMed

Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi

2014-03-01

We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

“Skill of Generalized Additive Model to Detect PM2.5 Health ...

EPA Pesticide Factsheets

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and by implication scales and periods that are not shared). Hospital admissions, meteorology (temperature and relative humidity), and air quality (PM2.5 and daily maximum ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from 2 days to greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study showed that GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good as a more complex model.Introduction. In the context of wavelet regression, confounding occurs when two or more independent variables interact with the dependent variable at the same frequency. Confounding also acts on a variety of time scales, changing the PM2.5 coefficient (magnitude and sign) and its significance ac

Critical scales to explain urban hydrological response: an application in Cranbrook, London

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick

2018-04-01

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

Coupled Modes over Indian Ocean at Sub-seasonal time Scales and its Prediction

NASA Astrophysics Data System (ADS)

Jung, E.; Kirtman, B. P.

2014-12-01

Sub-seasonal variability over the Indian Ocean, such as Madden-Julian Oscillation impacts weather and climate globally. However, the prediction of tropical sub-seasonal variability (TSV) remains a challenge, and understanding air-sea interactions on TSV time-scales is likely to be an important part of the prediction problem. The purpose of this paper is to examine the predictability of sub-seasonal variability in the tropical Indo-Pacific region. The analysis emphasizes on variability associated with coupled air-sea interactions in observational estimates, and how well these coupled modes are simulated and predicted within the context of a 30-year retrospective forecast experiment with a state-of-the-art atmosphere-ocean coupled model. The analysis shows that Sea Surface Temperature anomalies (SSTA) over the Indian Ocean tend to precede precipitation anomalies by 7-11 days with maximum amplitude over the Arabian Sea and the Bay of Bengal for summer and along the Seychelles-Chagos Thermocline Ridge (SCTR) region for winter. Though these coupled modes are captured by the models, the forecasts fail to predict its evolution. Based on the diagnosis of these coupled modes, we introduce a SCTR-SST index and an index that measures the modulation of the low-frequency amplitude (LFAM) of sub-seasonal SSTA variability over SCTR as a way to predict the coupled modes. Based on correlation with the observed variability, SCTR-SST has forecast skill of about 45 days over the Indian Ocean. However the sub-seasonal SSTAs in the predictions and the observational estimates do not have any direct ENSO tele-connection. In contrast, the LFAM of the sub-seasonal SSTA variance over SCTR is strongly correlated with ENSO, suggesting enhanced sub-seasonal variance on seasonal time-scales is potentially predictable.

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.

A stochastic fractional dynamics model of space-time variability of rain

NASA Astrophysics Data System (ADS)

Kundu, Prasun K.; Travis, James E.

2013-09-01

varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a statistical downscaling model per time-scale, 3 - summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Large-Scale Atmospheric Teleconnection Patterns Associated with the Interannual Variability of Heatwaves in East Asia and Its Decadal Changes

NASA Astrophysics Data System (ADS)

Choi, N.; Lee, M. I.; Lim, Y. K.; Kim, K. M.

2017-12-01

Heatwave is an extreme hot weather event which accompanies fatal damage to human health. The heatwave has a strong relationship with the large-scale atmospheric teleconnection patterns. In this study, we examine the spatial pattern of heatwave in East Asia by using the EOF analysis and the relationship between heatwave frequency and large-scale atmospheric teleconnection patterns. We also separate the time scale of heatwave frequency as the time scale longer than a decade and the interannual time scale. The long-term variation of heatwave frequency in East Asia shows a linkage with the sea surface temperature (SST) variability over the North Atlantic with a decadal time scale (a.k.a. the Atlantic Multidecadal Oscillation; AMO). On the other hands, the interannual variation of heatwave frequency is linked with the two dominant spatial patterns associated with the large-scale teleconnection patterns mimicking the Scandinavian teleconnection (SCAND-like) pattern and the circumglobal teleconnection (CGT-like) pattern, respectively. It is highlighted that the interannual variation of heatwave frequency in East Asia shows a remarkable change after mid-1990s. While the heatwave frequency was mainly associated with the CGT-like pattern before mid-1990s, the SCAND-like pattern becomes the most dominant one after mid-1990s, making the CGT-like pattern as the second. This study implies that the large-scale atmospheric teleconnection patterns play a key role in developing heatwave events in East Asia. This study further discusses possible mechanisms for the decadal change in the linkage between heatwave frequency and the large-scale teleconnection patterns in East Asia such as early melting of snow cover and/or weakening of East Asian jet stream due to global warming.

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

Urban catchments are typically characterised by a more flashy nature of the hydrological response compared to natural catchments. Predicting flow changes associated with urbanisation is not straightforward, as they are influenced by interactions between impervious cover, basin size, drainage connectivity and stormwater management infrastructure. In this study, we present an alternative approach to statistical analysis of hydrological response variability and basin flashiness, based on the distribution of inter-amount times. We analyse inter-amount time distributions of high-resolution streamflow time series for 17 (semi-)urbanised basins in North Carolina, USA, ranging from 13 to 238 km2 in size. We show that in the inter-amount-time framework, sampling frequency is tuned to the local variability of the flow pattern, resulting in a different representation and weighting of high and low flow periods in the statistical distribution. This leads to important differences in the way the distribution quantiles, mean, coefficient of variation and skewness vary across scales and results in lower mean intermittency and improved scaling. Moreover, we show that inter-amount-time distributions can be used to detect regulation effects on flow patterns, identify critical sampling scales and characterise flashiness of hydrological response. The possibility to use both the classical approach and the inter-amount-time framework to identify minimum observable scales and analyse flow data opens up interesting areas for future research.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Field-aligned currents' scale analysis performed with the Swarm constellation

NASA Astrophysics Data System (ADS)

Lühr, Hermann; Park, Jaeheung; Gjerloev, Jesper W.; Rauberg, Jan; Michaelis, Ingo; Merayo, Jose M. G.; Brauer, Peter

2015-01-01

We present a statistical study of the temporal- and spatial-scale characteristics of different field-aligned current (FAC) types derived with the Swarm satellite formation. We divide FACs into two classes: small-scale, up to some 10 km, which are carried predominantly by kinetic Alfvén waves, and large-scale FACs with sizes of more than 150 km. For determining temporal variability we consider measurements at the same point, the orbital crossovers near the poles, but at different times. From correlation analysis we obtain a persistent period of small-scale FACs of order 10 s, while large-scale FACs can be regarded stationary for more than 60 s. For the first time we investigate the longitudinal scales. Large-scale FACs are different on dayside and nightside. On the nightside the longitudinal extension is on average 4 times the latitudinal width, while on the dayside, particularly in the cusp region, latitudinal and longitudinal scales are comparable.

Bacterial community assembly in activated sludge: mapping beta diversity across environmental variables.

PubMed

Isazadeh, Siavash; Jauffur, Shameem; Frigon, Dominic

2016-12-01

Effect of ecological variables on community assembly of heterotrophic bacteria at eight full-scale and two pilot-scale activated sludge wastewater treatment plants (AS-WWTPs) were explored by pyrosequencing of 16S rRNA gene amplicons. In total, 39 samples covering a range of abiotic factors spread over space and time were analyzed. A core bacterial community of 24 families detected in at least six of the eight AS-WWTPs was defined. In addition to the core families, plant-specific families (observed at <50% AS-WWTPs) were found to be also important in the community structure. Observed beta diversity was partitioned with respect to ecological variables. Specifically, the following variables were considered: influent wastewater characteristics, season (winter vs. summer), process operations (conventional, oxidation ditch, and sequence batch reactor), reactor sizes (pilot-scale vs. full-scale reactors), chemical stresses defined by ozonation of return activated sludge, interannual variation, and geographical locations. Among the assessed variables, influent wastewater characteristics and geographical locations contributed more in explaining the differences between AS-WWTP bacterial communities with a maximum of approximately 26% of the observed variations. Partitioning of beta diversity is necessary to interpret the inherent variability in microbial community assembly and identify the driving forces at play in engineered microbial ecosystem. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Lighthouse in the dust: infrared echoes of periodic emission from massive black hole binaries★

NASA Astrophysics Data System (ADS)

D'Orazio, Daniel J.; Haiman, Zoltán

2017-09-01

The optical and UV emission from sub-parsec massive black hole binaries (MBHBs) in active galactic nuclei (AGNs) is believed to vary periodically, on time-scales comparable to the binary's orbital time. If driven by accretion rate fluctuations, the variability could be isotropic. If dominated by relativistic Doppler modulation, the variability should instead be anisotropic, resembling a rotating forward-beamed lighthouse. We consider the infrared (IR) reverberation of either type of periodic emission by pc-scale circumbinary dust tori. We predict the phase and amplitude of IR variability as a function of the ratio of dust light crossing time to the source variability period, and of the torus inclination and opening angle. We enumerate several differences between the isotropic and anisotropic cases. Interestingly, for a nearly face-on binary with an inclined dust torus, the Doppler boost can produce IR variability without any observable optical/UV variability. Such orphan-IR variability would have been missed in optical searches for periodic AGNs. We apply our models to time-domain WISE IR data from the MBHB candidate PG 1302-102 and find consistency with dust reverberation by both isotropically emitting and Doppler-boosted sources in the shorter wavelength W1-W2 (2.8 → 5.3 μm) bands. We constrain the dust torus to be thin (aspect ratio ˜ 0.1), with an inner radius at 1-5 pc. More generally, our dust-echo models will aid in identifying new MBHB candidates, determining their nature and constraining the physical properties of MBHBs and their dust tori.

The influence of spatially and temporally varying oceanographic conditions on meroplanktonic metapopulations

NASA Astrophysics Data System (ADS)

Botsford, L. W.; Moloney, C. L.; Hastings, A.; Largier, J. L.; Powell, T. M.; Higgins, K.; Quinn, J. F.

We synthesize the results of several modelling studies that address the influence of variability in larval transport and survival on the dynamics of marine metapopulations distributed along a coast. Two important benthic invertebrates in the California Current System (CCS), the Dungeness crab and the red sea urchin, are used as examples of the way in which physical oceanographic conditions can influence stability, synchrony and persistence of meroplanktonic metapopulations. We first explore population dynamics of subpopulations and metapopulations. Even without environmental forcing, isolated local subpopulations with density-dependence can vary on time scales roughly twice the generation time at high adult survival, shifting to annual time scales at low survivals. The high frequency behavior is not seen in models of the Dungeness crab, because of their high adult survival rates. Metapopulations with density-dependent recruitment and deterministic larval dispersal fluctuate in an asynchronous fashion. Along the coast, abundance varies on spatial scales which increase with dispersal distance. Coastwide, synchronous, random environmental variability tends to synchronize these metapopulations. Climate change could cause a long-term increase or decrease in mean larval survival, which in this model leads to greater synchrony or extinction respectively. Spatially managed metapopulations of red sea urchins go extinct when distances between harvest refugia become greater than the scale of larval dispersal. All assessments of population dynamics indicate that metapopulation behavior in general dependes critically on the temporal and spatial nature of larval dispersal, which is largely determined by physical oceanographic conditions. We therfore explore physical influences on larval dispersal patterns. Observed trends in temperature and salinity applied to laboratory-determined responses indicate that natural variability in temperature and salinity can lead to variability in larval development period on interannual (50%), intra-annual (20%) and latitudinal (200%) scales. Variability in development period significantly influences larval survival and, thus, net transport. Larval drifters that undertake diel vertical migration in a primitive equation model of coastal circulation (SPEM) demonstrate the importance of vertical migration in determining horizontal transport. Empirically derived estimates of the effects of wind forcing on larval transport of vertically migrating larvae (wind drift when near the surface and Ekman transport below the surface) match cross-shelf distributions in 4 years of existing larval data. We use a one-dimensional advection-diffusion model, which includes intra-annual timing of cross-shelf flows in the CCS, to explore the combined effects on settlement: (1) temperature- and salinity-dependent development and survival rates and (2) possible horizontal transport due to vertical migration of crab larvae. Natural variability in temperature, wind forcing, and the timing of the spring transition can cause the observed variability in recruitment. We conclude that understanding the dynamics of coastally distributed metapopulations in response to physically-induced variability in larval dispersal will be a critical step in assessing the effects of climate change on marine populations.

Scaling and universality in heart rate variability distributions

NASA Technical Reports Server (NTRS)

Rosenblum, M. G.; Peng, C. K.; Mietus, J. E.; Havlin, S.; Stanley, H. E.; Goldberger, A. L.

1998-01-01

We find that a universal homogeneous scaling form describes the distribution of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.

Scaling and universality in heart rate variability distributions

NASA Astrophysics Data System (ADS)

Ivanov, P. Ch; Rosenblum, M. G.; Peng, C.-K.; Mietus, J. E.; Havlin, S.; Stanley, H. E.; Goldberger, A. L.

We find that a universal homogeneous scaling form describes the distributions of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.

Long-term Variability of Beach Cusps

NASA Astrophysics Data System (ADS)

Pianca, C.; Holman, R. A.; Siegle, E.

2016-02-01

The most curious morphological features observed on beaches are the cusps. Due to their rhythmic spacing, beach cusps have attracted many observers and many, often contradictory, theories as to their form. Moreover, most of the research about beach cusps has focused on their formation. Few had available long time series to study such things as the variability of alongshore and cross-shore position and spacing on the cusp field, the presence, longevity and interactions between higher and lower sets of cusps, and the processes by which cusp fields extend, shrink or change length scale. The purpose of this work is to use long-term data sets of video images from two study sites, an intermediate (Duck, USA, 26 years) and a reflective beach (Massaguaçu, Brazil, 3 years), to investigate the temporal and spatial changes of cusps conditions. Time-evolving shoreline data were first extracted using an algorithm called ASLIM (Pianca et al 2015). Cusps were then identified based on the band-passed variability of time exposure image data about this shoreline as a function of elevation relative to MSL. The identified beaches cusps will be analyzed for cusp spacing, positions (upper or lower cusps), alongshore variability, merging events, percentage of cusp events, patterns of the events and time scales of variability. Finally, the relationship of these characteristics to environmental conditions (wave, tides, beach conditions) will be studied.

Variable classification in the LSST era: exploring a model for quasi-periodic light curves

NASA Astrophysics Data System (ADS)

Zinn, J. C.; Kochanek, C. S.; Kozłowski, S.; Udalski, A.; Szymański, M. K.; Soszyński, I.; Wyrzykowski, Ł.; Ulaczyk, K.; Poleski, R.; Pietrukowicz, P.; Skowron, J.; Mróz, P.; Pawlak, M.

2017-06-01

The Large Synoptic Survey Telescope (LSST) is expected to yield ˜107 light curves over the course of its mission, which will require a concerted effort in automated classification. Stochastic processes provide one means of quantitatively describing variability with the potential advantage over simple light-curve statistics that the parameters may be physically meaningful. Here, we survey a large sample of periodic, quasi-periodic and stochastic Optical Gravitational Lensing Experiment-III variables using the damped random walk (DRW; CARMA(1,0)) and quasi-periodic oscillation (QPO; CARMA(2,1)) stochastic process models. The QPO model is described by an amplitude, a period and a coherence time-scale, while the DRW has only an amplitude and a time-scale. We find that the periodic and quasi-periodic stellar variables are generally better described by a QPO than a DRW, while quasars are better described by the DRW model. There are ambiguities in interpreting the QPO coherence time due to non-sinusoidal light-curve shapes, signal-to-noise ratio, error mischaracterizations and cadence. Higher order implementations of the QPO model that better capture light-curve shapes are necessary for the coherence time to have its implied physical meaning. Independent of physical meaning, the extra parameter of the QPO model successfully distinguishes most of the classes of periodic and quasi-periodic variables we consider.

Long term variability of B supergiant winds

NASA Technical Reports Server (NTRS)

Massa, Derck L.

1995-01-01

The object of this observing proposal was to sample wind variability in B supergiants on a daily basis over a period of several days in order to determine the time scale with which density variability occurs in their winds. Three stars were selected for this project: 69 Cyg (B0 Ib), HD 164402 (B0 Ib), and HD 47240 (B1 Ib). Three grey scale representations of the Si IV lambda lambda 1400 doublet in each star are attached. In these figures, time (in days) increases upward, and the wavelength (in terms of velocity relative to the rest wavelength of the violet component of the doublet) is the abscissa. The spectra are normalized by a minimum absorption (maximum flux) template, so that all changes appear as absorptions. As a result of these observations, we can now state with some certainty that typical B supergiants develop significant wind inhomogeneities with recurrence times of a few days, and that some of these events show signs of strong temporal coherence.

Epidemic spreading on activity-driven networks with attractiveness.

PubMed

Pozzana, Iacopo; Sun, Kaiyuan; Perra, Nicola

2017-10-01

We study SIS epidemic spreading processes unfolding on a recent generalization of the activity-driven modeling framework. In this model of time-varying networks, each node is described by two variables: activity and attractiveness. The first describes the propensity to form connections, while the second defines the propensity to attract them. We derive analytically the epidemic threshold considering the time scale driving the evolution of contacts and the contagion as comparable. The solutions are general and hold for any joint distribution of activity and attractiveness. The theoretical picture is confirmed via large-scale numerical simulations performed considering heterogeneous distributions and different correlations between the two variables. We find that heterogeneous distributions of attractiveness alter the contagion process. In particular, in the case of uncorrelated and positive correlations between the two variables, heterogeneous attractiveness facilitates the spreading. On the contrary, negative correlations between activity and attractiveness hamper the spreading. The results presented contribute to the understanding of the dynamical properties of time-varying networks and their effects on contagion phenomena unfolding on their fabric.

Interannual variability in phytoplankton pigment distribution during the spring transition along the west coast of North America

NASA Technical Reports Server (NTRS)

Thomas, A. C.; Strub, P. T.

1989-01-01

A 5-year time series of coastal zone color scanner imagery (1980-1983, 1986) is used to examine changes in the large-scale pattern of chlorophyll pigment concentration coincident with the spring transition in winds and currents along the west coast of North America. The data show strong interannual variability in the timing and spatial patterns of pigment concentration at the time of the transition event. Interannual variability in the response of pigment concentration to the spring transition appears to be a function of spatial and temporal variability in vertical nutrient flux induced by wind mixing and/or the upwelling initiated at the time of the transition. Interannual differences in the mixing regime are illustrated with a one-dimensional mixing model.

X-ray flaring in PDS 456 observed in a high-flux state

NASA Astrophysics Data System (ADS)

Matzeu, G. A.; Reeves, J. N.; Nardini, E.; Braito, V.; Turner, T. J.; Costa, M. T.

2017-03-01

We present an analysis of a 190 ks (net exposure) Suzaku observation, carried out in 2007, of the nearby (z = 0.184) luminous (Lbol ˜ 1047 erg s-1) quasar PDS 456. In this observation, the intrinsically steep bare continuum is revealed compared to subsequent observations, carried out in 2011 and 2013, where the source is fainter, harder and more absorbed. We detected two pairs of prominent hard and soft flares, restricted to the first and second halves of the observation, respectively. The flares occur on time-scales of the order of ˜50 ks, which is equivalent to a light-crossing distance of ˜10 Rg in PDS 456. From the spectral variability observed during the flares, we find that the continuum changes appear to be dominated by two components: (I) a variable soft component (<2 keV), which may be related to the Comptonized tail of the disc emission, and (II) a variable hard power-law component (>2 keV). The photon index of the latter power-law component appears to respond to changes in the soft band flux, increasing during the soft X-ray flares. Here, the softening of the spectra, observed during the flares, may be due to Compton cooling of the disc corona induced by the increased soft X-ray photon seed flux. In contrast, we rule out partial covering absorption as the physical mechanism behind the observed short time-scale spectral variability, as the time-scales are likely too short to be accounted for by absorption variability.

Cortical activity is more stable when sensory stimuli are consciously perceived

PubMed Central

Schurger, Aaron; Sarigiannidis, Ioannis; Naccache, Lionel; Sitt, Jacobo D.; Dehaene, Stanislas

2015-01-01

According to recent evidence, stimulus-tuned neurons in the cerebral cortex exhibit reduced variability in firing rate across trials, after the onset of a stimulus. However, in order for a reduction in variability to be directly relevant to perception and behavior, it must be realized within trial—the pattern of activity must be relatively stable. Stability is characteristic of decision states in recurrent attractor networks, and its possible relevance to conscious perception has been suggested by theorists. However, it is difficult to measure on the within-trial time scales and broadly distributed spatial scales relevant to perception. We recorded simultaneous magneto- and electroencephalography (MEG and EEG) data while subjects observed threshold-level visual stimuli. Pattern-similarity analyses applied to the data from MEG gradiometers uncovered a pronounced decrease in variability across trials after stimulus onset, consistent with previous single-unit data. This was followed by a significant divergence in variability depending upon subjective report (seen/unseen), with seen trials exhibiting less variability. Applying the same analysis across time, within trial, we found that the latter effect coincided in time with a difference in the stability of the pattern of activity. Stability alone could be used to classify data from individual trials as “seen” or “unseen.” The same metric applied to EEG data from patients with disorders of consciousness exposed to auditory stimuli diverged parametrically according to clinically diagnosed level of consciousness. Differences in signal strength could not account for these results. Conscious perception may involve the transient stabilization of distributed cortical networks, corresponding to a global brain-scale decision. PMID:25847997

Characterizing the temporal variability of L-band backscatter using dense UAVSAR time-series in preparation for the NISAR mission

NASA Astrophysics Data System (ADS)

Lavalle, M.; Lee, A.; Shiroma, G. X. H.; Rosen, P. A.

2017-12-01

The NASA-ISRO SAR (NISAR) mission will deliver unprecedented global maps of L-band HH/HV backscatter every 12 days with resolution ranging from a few to tens of meters in support of ecosystem, solid Earth and cryosphere science and applications. Understanding and modeling the temporal variability of L-band backscatter over temporal scales of years, months and days is critical for developing retrieval algorithms that can robustly extract the biophysical variables of interest (e.g., forest biomass, soil moisture, etc.) from NISAR time series. In this talk, we will focus on the 5-year time series of 60 JPL/UAVSAR polarimetric images collected near the Sacramento Delta to characterize the inter-annual, seasonal and short-scale variability of the L-band polarimetric backscatter for a broad range of land cover types. Our preliminary analysis reveals that backscatter from man-made structures is very stable over time, whereas backscatter from bare soil and herbaceous vegetation fluctuates over time with standard deviation of 2.3 dB. Land-cover classes with larger biomass such as trees and tall vegetation show about 1.5 dB standard deviation in temporal backscatter variability. Closer examination of high-spatial resolution UAVSAR imagery reveal also that vegetation structure, speckle noise and horizontal forest heterogeneity in the Sacramento Delta area can significantly affect the point-wise backscatter value. In our talk, we will illustrate the long UAVSAR time series, describe our data analysis strategy, show the results of polarimetric variability for different land cover classes and number of looks, and discuss the implications for the development of NISAR L2/L3 retrieval algorithms of ecosystem science.

Using variance structure to quantify responses to perturbation in fish catches

USGS Publications Warehouse

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Uncovering the Anthropogenic Sea Level Change using an Improved Sea Level Reconstruction for the Indian Ocean

NASA Astrophysics Data System (ADS)

Kumar, P.; Hamlington, B.; Thompson, P. R.; Han, W.

2016-12-01

Despite having some of the world's most densely populated and vulnerable coastal regions, sea level (SL) variability in the Indian Ocean (IO) has received considerably less attention than the Pacific Ocean. Differentiating the internal variability from the long-term trend in global mean sea level (GMSL) at decadal time-scales is vital for planning and mitigation efforts in the IO region. Understanding the dynamics of internal and anthropogenic SL change is essential for understanding the dynamic pathways that link the IO basin to terrestrial climates world-wide. With a sparse pre-satellite observational record of the IO, the Indo-Pacific internal climate variability is difficult to represent accurately. However, an improved representation of pre-satellite SL variability can be achieved by using a multivariate reconstruction technique. By using cyclostationary empirical orthogonal functions (CSEOFs) that can capture time-varying spatial patterns, gaps in the historical record when observations are sparse are filled using spatial relationships from time periods when the observational network is dense. This reconstruction method combines SL data and sea surface temperature (SST) to create a SL reconstruction that spans a period from 1900 to present, long enough to study climate signals over interannual to decadal time scales. This study aims at estimating the component of SL rise that relates to anthropogenic forcing by identifying and removing the fraction related to internal variability. An improved understanding of how the internal climate variability can affect the IO SL trend and variability, will provide an insight into the future SL changes. It is also important to study links between SL and climate variability in the past to understand how SL will respond to similar climatic events in the future and if this response will be influenced by the changing climate.

Relationship between the Arctic oscillation and surface air temperature in multi-decadal time-scale

NASA Astrophysics Data System (ADS)

Tanaka, Hiroshi L.; Tamura, Mina

2016-09-01

In this study, a simple energy balance model (EBM) was integrated in time, considering a hypothetical long-term variability in ice-albedo feedback mimicking the observed multi-decadal temperature variability. A natural variability was superimposed on a linear warming trend due to the increasing radiative forcing of CO2. The result demonstrates that the superposition of the natural variability and the background linear trend can offset with each other to show the warming hiatus for some period. It is also stressed that the rapid warming during 1970-2000 can be explained by the superposition of the natural variability and the background linear trend at least within the simple model. The key process of the fluctuating planetary albedo in multi-decadal time scale is investigated using the JRA-55 reanalysis data. It is found that the planetary albedo increased for 1958-1970, decreased for 1970-2000, and increased for 2000-2012, as expected by the simple EBM experiments. The multi-decadal variability in the planetary albedo is compared with the time series of the AO mode and Barents Sea mode of surface air temperature. It is shown that the recent AO negative pattern showing warm Arctic and cold mid-latitudes is in good agreement with planetary albedo change indicating negative anomaly in high latitudes and positive anomaly in mid-latitudes. Moreover, the Barents Sea mode with the warm Barents Sea and cold mid-latitudes shows long-term variability similar to planetary albedo change. Although further studies are needed, the natural variabilities of both the AO mode and Barents Sea mode indicate some possible link to the planetary albedo as suggested by the simple EBM to cause the warming hiatus in recent years.

Hydrographical variability and major ecosystem changes as recorded in the growth of Arctica islandica from the northern North Sea

NASA Astrophysics Data System (ADS)

Trofimova, Tamara; Andersson, Carin; Bonitz, Fabian

2017-04-01

Reconstruction of marine climate variability on regional to global scales requires a network of climatically sensitive annually resolved archives from key oceanographic locations. The small number of records existing to date impedes the application of a network approach. In this study, we aim at improving the spatial coverage of annually resolved paleo proxy records by investigating the impact of climate variability on sclerochronological records of A. islandica from the Viking Bank in the northern North Sea. The northern North Sea has an excellent oceanographic setting because its hydrography is primarily controlled by the major Atlantic water inflow to the North Sea. Using annual growth increment measurements of 30 shells we constructed a 265-year shell-growth chronology spanning the time interval AD 1748-2013. Chronology statistics (Rbar (>0.5) and EPS (>0.85)) indicate a robust signal of a common environmental forcing controlling shell growth for the major part of the record. Comparison with other sclerochronologies from the oceanographically related locations reveals a coherency on longer time scales, which is likely a response to a common environmental driver or a combination of such drivers. No significant correlation on the year-on-year level has been found between the chronology and time series of temperature and salinity from the area close to the study site. However, the timing of major hydrographical anomalies described for the region (Great Salinity Anomalies) coincide with a decrease in shell growth; likely in response to an impact on lower trophic levels, i.e. plankton composition and abundance. Spectral analysis of the chronology reveals a 21-26 year periodicity recorded in the shell growth. The variability on a similar time scale has been observed in multiple records from the North Atlantic and in model outputs. It has been suggested to represent one of the dominant scales of multi-decadal variability especially pronounced prior to the 20th century. In our chronology this variability is clearly observed prior to the 1920's and fades out towards present day. This change coincides with the most significant regime shift in the North Atlantic observed in the 20th-century, connected with dramatic warming and increasing Atlantic inflow. Hence, our data show that growth chronology from the Viking Bank region has a high potential to be used in climate variability studies and can significantly contribute to the development of a spatial sclerochronological network.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Solar Cycle in the Heliosphere and Cosmic Rays

DTIC Science & Technology

2014-10-23

at the source surface at 2.5 solar radii around the Sun. OMF shows a great variability both in solar cycle and on the centennial scale (see Fig. 3...It is important to note that the centennial variability is great (Lockwood et al. 1999; Solanki et al. 2000) comparable with or even greater than the...be identified as spikes in production of cosmogenic isotope (10Be and 14C) records on the centennial -millennial time scale (e.g., Usoskin and

Performance of an attention-demanding task during treadmill walking shifts the noise qualities of step-to-step variation in step width.

PubMed

Grabiner, Mark D; Marone, Jane R; Wyatt, Marilynn; Sessoms, Pinata; Kaufman, Kenton R

2018-06-01

The fractal scaling evident in the step-to-step fluctuations of stepping-related time series reflects, to some degree, neuromotor noise. The primary purpose of this study was to determine the extent to which the fractal scaling of step width, step width and step width variability are affected by performance of an attention-demanding task. We hypothesized that the attention-demanding task would shift the structure of the step width time series toward white, uncorrelated noise. Subjects performed two 10-min treadmill walking trials, a control trial of undisturbed walking and a trial during which they performed a mental arithmetic/texting task. Motion capture data was converted to step width time series, the fractal scaling of which were determined from their power spectra. Fractal scaling decreased by 22% during the texting condition (p < 0.001) supporting the hypothesized shift toward white uncorrelated noise. Step width and step width variability increased 19% and five percent, respectively (p < 0.001). However, a stepwise discriminant analysis to which all three variables were input revealed that the control and dual task conditions were discriminated only by step width fractal scaling. The change of the fractal scaling of step width is consistent with increased cognitive demand and suggests a transition in the characteristics of the signal noise. This may reflect an important advance toward the understanding of the manner in which neuromotor noise contributes to some types of falls. However, further investigation of the repeatability of the results, the sensitivity of the results to progressive increases in cognitive load imposed by attention-demanding tasks, and the extent to which the results can be generalized to the gait of older adults seems warranted. Copyright © 2018 Elsevier B.V. All rights reserved.

Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest.

PubMed

Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena; Dufrêne, Eric

2016-04-01

Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Decomposition of Time Scales in Linear Systems and Markovian Decision Processes.

DTIC Science & Technology

1980-11-01

this research. I, 3 iv U TABLE OF CONTENTS *Chapter Page *-1. INTRODUCTION .................................................. 1 2. EIGENSTRUCTTJRE...Components ..... o....... 16 2.4. Ordering of State Variables.. ......... ........ 20 2.5. Example - 8th Order Power System Model................ 22 3 ...results. In Chapter 3 we consider the time scale decomposition of singularly perturbed systems. For this problem (1.1) takes the form 12 + u (1.4) 2

USING CMAQ FOR EXPOSURE MODELING AND CHARACTERIZING THE SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES

EPA Science Inventory

Atmospheric processes and the associated transport and dispersion of atmospheric pollutants are known to be highly variable in time and space. Current air quality models that characterize atmospheric chemistry effects, e.g. the Community Multi-scale Air Quality (CMAQ), provide vo...

Effects of task and age on the magnitude and structure of force fluctuations: insights into underlying neuro-behavioral processes.

PubMed

Vieluf, Solveig; Temprado, Jean-Jacques; Berton, Eric; Jirsa, Viktor K; Sleimen-Malkoun, Rita

2015-03-13

The present study aimed at characterizing the effects of increasing (relative) force level and aging on isometric force control. To achieve this objective and to infer changes in the underlying control mechanisms, measures of information transmission, as well as magnitude and time-frequency structure of behavioral variability were applied to force-time-series. Older adults were found to be weaker, more variable, and less efficient than young participants. As a function of force level, efficiency followed an inverted-U shape in both groups, suggesting a similar organization of the force control system. The time-frequency structure of force output fluctuations was only significantly affected by task conditions. Specifically, a narrower spectral distribution with more long-range correlations and an inverted-U pattern of complexity changes were observed with increasing force level. Although not significant older participants displayed on average a less complex behavior for low and intermediate force levels. The changes in force signal's regularity presented a strong dependence on time-scales, which significantly interacted with age and condition. An inverted-U profile was only observed for the time-scale relevant to the sensorimotor control process. However, in both groups the peak was not aligned with the optimum of efficiency. Our results support the view that behavioral variability, in terms of magnitude and structure, has a functional meaning and affords non-invasive markers of the adaptations of the sensorimotor control system to various constraints. The measures of efficiency and variability ought to be considered as complementary since they convey specific information on the organization of control processes. The reported weak age effect on variability and complexity measures suggests that the behavioral expression of the loss of complexity hypothesis is not as straightforward as conventionally admitted. However, group differences did not completely vanish, which suggests that age differences can be more or less apparent depending on task properties and whether difficulty is scaled in relative or absolute terms.

Variability of the Denmark Strait overflow: Moored time series from 1996-2011

NASA Astrophysics Data System (ADS)

Jochumsen, Kerstin; Quadfasel, Detlef; Valdimarsson, Heã°Inn; Jónsson, SteingríMur

2012-12-01

The Denmark Strait overflow provides about half of the total dense water overflow from the Nordic Seas into the North Atlantic Ocean. The velocity of the overflow has been monitored in the Strait with two moored Acoustic Doppler Current Profilers since 1996 with several interruptions due to mooring losses or instrument failure. So far, overflow transports were only calculated when data from both moorings were available. In this work, we introduce a linear model to fill gaps in the time series when data from only one instrument is available. The mean overflow transport is 3.4 Sv and exhibits a variance of 2.0 Sv2. No significant trend was detected in the time series. The highest variability in the transport is associated with the passage of mesoscale eddies with time scales of 2-10 days (associated with a variance of 1.5 Sv2). Seasonal variability is weak and explains less than 5% of the variance in all time series, which is in contrast to the strong seasonal cycle found in high resolution model simulations. Interannual variability is on the order of 10% of the mean. A relation to atmospheric forcing such as the local wind stress curl, as well as to larger scale phenomena, e.g. the North Atlantic Oscillation, is not detected. Since 2005 data from moored temperature, conductivity and pressure recorders have been available as well, monitoring the hydrographic variability at the bottom of Denmark Strait. In recent years the temperature time series of the Denmark Strait overflow revealed a cooling, while the salinity stayed nearly constant.

Process connectivity in a naturally prograding river delta

NASA Astrophysics Data System (ADS)

Sendrowski, Alicia; Passalacqua, Paola

2017-03-01

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

Large-eddy simulation of a turbulent mixing layer

NASA Technical Reports Server (NTRS)

Mansour, N. N.; Ferziger, J. H.; Reynolds, W. C.

1978-01-01

The three dimensional, time dependent (incompressible) vorticity equations were used to simulate numerically the decay of isotropic box turbulence and time developing mixing layers. The vorticity equations were spatially filtered to define the large scale turbulence field, and the subgrid scale turbulence was modeled. A general method was developed to show numerical conservation of momentum, vorticity, and energy. The terms that arise from filtering the equations were treated (for both periodic boundary conditions and no stress boundary conditions) in a fast and accurate way by using fast Fourier transforms. Use of vorticity as the principal variable is shown to produce results equivalent to those obtained by use of the primitive variable equations.

Evidence for the timing of sea-level events during MIS 3

NASA Astrophysics Data System (ADS)

Siddall, M.

2005-12-01

Four large sea-level peaks of millennial-scale duration occur during MIS 3. In addition smaller peaks may exist close to the sensitivity of existing methods to derive sea level during these periods. Millennial-scale changes in temperature during MIS 3 are well documented across much of the planet and are linked in some unknown, yet fundamental way to changes in ice volume / sea level. It is therefore highly likely that the timing of the sea level events during MIS 3 will prove to be a `Rosetta Stone' for understanding millennial scale climate variability. I will review observational and mechanistic arguments for the variation of sea level on Antarctic, Greenland and absolute time scales.

A scheme for recording a fast process at nanosecond scale by using digital holographic interferometry with continuous wave laser

NASA Astrophysics Data System (ADS)

Wang, Jun; Zhao, Jianlin; Di, Jianglei; Jiang, Biqiang

2015-04-01

A scheme for recording fast process at nanosecond scale by using digital holographic interferometry with continuous wave (CW) laser is described and demonstrated experimentally, which employs delayed-time fibers and angular multiplexing technique and can realize the variable temporal resolution at nanosecond scale and different measured depths of object field at certain temporal resolution. The actual delay-time is controlled by two delayed-time fibers with different lengths. The object field information in two different states can be simultaneously recorded in a composite hologram. This scheme is also suitable for recording fast process at picosecond scale, by using an electro-optic modulator.

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity.

PubMed

Tippett, Michael K; Cohen, Joel E

2016-02-29

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from 'outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954-2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related.

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity

PubMed Central

Tippett, Michael K.; Cohen, Joel E.

2016-01-01

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from ‘outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954–2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related. PMID:26923210

Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Cohen, Joel E.

2016-02-01

Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from `outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954-2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related.

Continuous intestinal infusion of levodopa-carbidopa in patients with advanced Parkinson's disease in Spain: Subanalysis by autonomous community.

PubMed

Santos-García, D; Catalán, M J; Puente, V; Valldeoriola, F; Regidor, I; Mir, P; Matías-Arbelo, J; Parra, J C; Grandas, F

2018-01-12

To compare the characteristics of patients undergoing treatment with continuous intestinal infusion of levodopa-carbidopa (CIILC) for advanced Parkinson's disease and the data on the effectiveness and safety of CIILC in the different autonomous communities (AC) of Spain. A retrospective, longitudinal, observational study was carried out into 177 patients from 11 CAs who underwent CIILC between January 2006 and December 2011. We analysed data on patients' clinical and demographic characteristics, variables related to effectiveness (changes in off time/on time with or without disabling dyskinesia; changes in Hoehn and Yahr scale and Unified Parkinson's Disease Rating Scale scores; non-motor symptoms; and Clinical Global Impression scale scores) and safety (adverse events), and the rate of CIILC discontinuation. Significant differences were observed between CAs for several baseline variables: duration of disease progression prior to CIILC onset, off time (34.9-59.7%) and on time (2.6-48.0%; with or without disabling dyskinesia), Hoehn and Yahr score during on time, Unified Parkinson's Disease Rating Scale-III score during both on and off time, presence of≥ 4 motor symptoms, and CIILC dose. Significant differences were observed during follow-up (> 24 months in 9 of the 11 CAs studied) for the percentage of off time and on time without disabling dyskinesia, adverse events frequency, and Clinical Global Impression scores. The rate of CIILC discontinuation was between 20-40% in 9 CAs (78 and 80% in remaining 2 CAs). This study reveals a marked variability between CAs in terms of patient selection and CIILC safety and effectiveness. These results may have been influenced by patients' baseline characteristics, the availability of multidisciplinary teams, and clinical experience. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

The Stochastic predictability limits of GCM internal variability and the Stochastic Seasonal to Interannual Prediction System (StocSIPS)

NASA Astrophysics Data System (ADS)

Del Rio Amador, Lenin; Lovejoy, Shaun

2017-04-01

Over the past ten years, a key advance in our understanding of atmospheric variability is the discovery that between the weather and climate regime lies an intermediate "macroweather" regime, spanning the range of scales from ≈10 days to ≈30 years. Macroweather statistics are characterized by two fundamental symmetries: scaling and the factorization of the joint space-time statistics. In the time domain, the scaling has low intermittency with the additional property that successive fluctuations tend to cancel. In space, on the contrary the scaling has high (multifractal) intermittency corresponding to the existence of different climate zones. These properties have fundamental implications for macroweather forecasting: a) the temporal scaling implies that the system has a long range memory that can be exploited for forecasting; b) the low temporal intermittency implies that mathematically well-established (Gaussian) forecasting techniques can be used; and c), the statistical factorization property implies that although spatial correlations (including teleconnections) may be large, if long enough time series are available, they are not necessarily useful in improving forecasts. Theoretically, these conditions imply the existence of stochastic predictability limits in our talk, we show that these limits apply to GCM's. Based on these statistical implications, we developed the Stochastic Seasonal and Interannual Prediction System (StocSIPS) for the prediction of temperature from regional to global scales and from one month to many years horizons. One of the main components of StocSIPS is the separation and prediction of both the internal and externally forced variabilities. In order to test the theoretical assumptions and consequences for predictability and predictions, we use 41 different CMIP5 model outputs from preindustrial control runs that have fixed external forcings: whose variability is purely internally generated. We first show that these statistical assumptions hold with relatively good accuracy and then we performed hindcasts at global and regional scales from monthly to annual time resolutions using StocSIPS. We obtained excellent agreement between the hindcast Mean Square Skill Score (MSSS) and the theoretical stochastic limits. We also show the application of StocSIPS to the prediction of average global temperature and compare our results with those obtained using multi-model ensemble approaches. StocSIPS has numerous advantages including a) higher MSSS for large time horizons, b) the from convergence to the real - not model - climate, c) much higher computational speed, d) no need for data assimilation, e) no ad hoc post processing and f) no need for downscaling.

Space and time variability of the surface color field in the northern Adriatic Sea

NASA Technical Reports Server (NTRS)

Barale, Vittorio; Mcclain, Charles R.; Malanotte-Rizzoli, Paola

1986-01-01

A time series of coastal zone color scanner images for the years 1979 and 1980 was used to observe the spatial and temporal variability of bio-optical processes and circulation patterns of the northern Adriatic Sea on monthly, seasonal, and interannual scales. The chlorophyll-like pigment concentrations derived from satellite data exhibited a high correlation with sea truth measurements performed during seven surveys in the summer of both years. Comparison of the mean pigment fields indicates a general increase in concentration values and larger scales of coastal features from 1979 to 1980. This variability may be linked to the different patterns of nutrient influx due to coastal runoff in the 2 years. The distribution of surface features is consistent with the general cyclonic circulation pattern. The pigment heterogeneity appears to be governed by fluctuations of freshwater discharge, while the dominant wind fields do not appear to have important direct effects. The Po River presents a plume spreading predominantly in a southeastern direction, with scales positively correlated with its outflow. The spatial scales of the western coastal layer, in contrast, are negatively correlated with this outflow and the plume scales. Both results are consistent with, and may be rationalized by, recent theoretical and experimental results involving a dynamical balance between nonlinear advection and bottom friction, with alternate predominance of one of the two effects.

The land-use legacy effect: Towards a mechanistic understanding of time-lagged water quality responses to land use/cover.

PubMed

Martin, Sherry L; Hayes, Daniel B; Kendall, Anthony D; Hyndman, David W

2017-02-01

Numerous studies have linked land use/land cover (LULC) to aquatic ecosystem responses, however only a few have included the dynamics of changing LULC in their analysis. In this study, we explicitly recognize changing LULC by linking mechanistic groundwater flow and travel time models to a historical time series of LULC, creating a land-use legacy map. We then illustrate the utility of legacy maps to explore relationships between dynamic LULC and lake water chemistry. We tested two main concepts about mechanisms linking LULC and lake water chemistry: groundwater pathways are an important mechanism driving legacy effects; and, LULC over multiple spatial scales is more closely related to lake chemistry than LULC over a single spatial scale. We applied statistical models to twelve water chemistry variables, ranging from nutrients to relatively conservative ions, to better understand the roles of biogeochemical reactivity and solubility on connections between LULC and aquatic ecosystem response. Our study illustrates how different areas can have long groundwater pathways that represent different LULC than what can be seen on the landscape today. These groundwater pathways delay the arrival of nutrients and other water quality constituents, thus creating a legacy of historic land uses that eventually reaches surface water. We find that: 1) several water chemistry variables are best fit by legacy LULC while others have a stronger link to current LULC, and 2) single spatial scales of LULC analysis performed worse for most variables. Our novel combination of temporal and spatial scales was the best overall model fit for most variables, including SRP where this model explained 54% of the variation. We show that it is important to explicitly account for temporal and spatial context when linking LULC to ecosystem response. Copyright © 2016. Published by Elsevier B.V.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

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.

The effects of noise on binocular rivalry waves: a stochastic neural field model

NASA Astrophysics Data System (ADS)

Webber, Matthew A.; Bressloff, Paul C.

2013-03-01

We analyze the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We first show how, in the absence of any noise, the system supports a propagating composite wave consisting of an invading activity front in one network co-moving with a retreating front in the other network. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how extrinsic noise in the activity variables leads to a diffusive-like displacement (wandering) of the composite wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. We use our analysis to calculate the first-passage-time distribution for a stochastic rivalry wave to travel a fixed distance, which we find to be given by an inverse Gaussian. Finally, we investigate the effects of noise in the depression variables, which under an adiabatic approximation lead to quenched disorder in the neural fields during propagation of a wave.

Brightness Variations in the Solar Atmosphere as Seen by SOHO

NASA Astrophysics Data System (ADS)

Brkovic, A.; Rüedi, I.; Solanki, S. K.; Huber, M. C. E.; Stenflo, J. O.; Stucki, K.; Harrison, R.; Fludra, A.

We present preliminary results of a statistical analysis of the brightness variations of solar features at different levels in the solar atmosphere. We observed quiet Sun regions at disc centre using the Coronal Diagnostic Spectrometer (CDS) onboard the Solar and Heliospheric Observatory (SOHO). We find significant variability at all time scales in all parts of the quiet Sun, from darkest intranetwork to brightest network. Such variations are observed simultaneously in the chromospheric He I 584.33 Angstroms (2 \\cdot 10^4 K) line, the transition region O V 629.74 Angstroms (2.5 \\cdot 10^5 K) and coronal Mg IX 368.06 Angstroms (10^6 K) line. The relative variability is independent of brightness and most of the variability appears to take place on time scales longer than 5 minutes for all 3 spectral lines. No significant differences are observed between the different data sets.

Coordinated Multiwavelength Observations of PKS 0528+134 in Quiescence

NASA Astrophysics Data System (ADS)

Boettcher, Markus; Palma, N.

2011-01-01

We report results of an intensive multiwavelength campaign on the prominent high-redshift (z = 2.06) gamma-ray bright blazar PKS 0528+134 in September - October 2009. The campaign was centered on four 30 ksec pointings with XMM-Newton, supplemented with ground-based optical (MDM, Perkins) and radio (UMRAO, Medicina, Metsaehovi, Noto, SMA) observations as well as long-term X-ray monitoring with RXTE and gamma-ray monitoring by Fermi. We find significant variability on 1 day time scales in the optical regime, accompanied by a weak redder-when-brighter trend. X-ray variability is found on longer ( 1 week) time scales, while the Fermi light curve shows no evidence for variability, neither in flux nor spectral index. We constructed four simultaneous spectral energy distributions, which can all be fit satisfactorily with a one-zone leptonic jet model. This work was supported by NASA through XMM-Newton Guest Observer Grant NNX09AV45G.

Multiscale entropy analysis of heart rate variability in heart failure, hypertensive, and sinoaortic-denervated rats: classical and refined approaches.

PubMed

Silva, Luiz Eduardo Virgilio; Lataro, Renata Maria; Castania, Jaci Airton; da Silva, Carlos Alberto Aguiar; Valencia, Jose Fernando; Murta, Luiz Otavio; Salgado, Helio Cesar; Fazan, Rubens; Porta, Alberto

2016-07-01

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation. Copyright © 2016 the American Physiological Society.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Time-dependent scaling patterns in high frequency financial data

NASA Astrophysics Data System (ADS)

Nava, Noemi; Di Matteo, Tiziana; Aste, Tomaso

2016-10-01

We measure the influence of different time-scales on the intraday dynamics of financial markets. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures of complexity: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices of various stock market indices. Our results reveal intraday trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multifractal nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the opening and at the closing of the session. We demonstrate that these patterns are statistically significant, robust, reproducible and characteristic of each stock market. We argue that any modelling, analytics or trading strategy must take into account these non-stationary intraday scaling patterns.

An observational method for fast stochastic X-ray polarimetry timing

NASA Astrophysics Data System (ADS)

Ingram, Adam R.; Maccarone, Thomas J.

2017-11-01

The upcoming launch of the first space based X-ray polarimeter in ˜40 yr will provide powerful new diagnostic information to study accreting compact objects. In particular, analysis of rapid variability of the polarization degree and angle will provide the opportunity to probe the relativistic motions of material in the strong gravitational fields close to the compact objects, and enable new methods to measure black hole and neutron star parameters. However, polarization properties are measured in a statistical sense, and a statistically significant polarization detection requires a fairly long exposure, even for the brightest objects. Therefore, the sub-minute time-scales of interest are not accessible using a direct time-resolved analysis of polarization degree and angle. Phase-folding can be used for coherent pulsations, but not for stochastic variability such as quasi-periodic oscillations. Here, we introduce a Fourier method that enables statistically robust detection of stochastic polarization variability for arbitrarily short variability time-scales. Our method is analogous to commonly used spectral-timing techniques. We find that it should be possible in the near future to detect the quasi-periodic swings in polarization angle predicted by Lense-Thirring precession of the inner accretion flow. This is contingent on the mean polarization degree of the source being greater than ˜4-5 per cent, which is consistent with the best current constraints on Cygnus X-1 from the late 1970s.

The Geometric Phase of Stock Trading.

PubMed

Altafini, Claudio

2016-01-01

Geometric phases describe how in a continuous-time dynamical system the displacement of a variable (called phase variable) can be related to other variables (shape variables) undergoing a cyclic motion, according to an area rule. The aim of this paper is to show that geometric phases can exist also for discrete-time systems, and even when the cycles in shape space have zero area. A context in which this principle can be applied is stock trading. A zero-area cycle in shape space represents the type of trading operations normally carried out by high-frequency traders (entering and exiting a position on a fast time-scale), while the phase variable represents the cash balance of a trader. Under the assumption that trading impacts stock prices, even zero-area cyclic trading operations can induce geometric phases, i.e., profits or losses, without affecting the stock quote.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

The Impact of ARM on Climate Modeling. Chapter 26

NASA Technical Reports Server (NTRS)

Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

2016-01-01

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

Multifractal cross-correlation effects in two-variable time series of complex network vertex observables

NASA Astrophysics Data System (ADS)

OświÈ©cimka, Paweł; Livi, Lorenzo; DroŻdŻ, Stanisław

2016-10-01

We investigate the scaling of the cross-correlations calculated for two-variable time series containing vertex properties in the context of complex networks. Time series of such observables are obtained by means of stationary, unbiased random walks. We consider three vertex properties that provide, respectively, short-, medium-, and long-range information regarding the topological role of vertices in a given network. In order to reveal the relation between these quantities, we applied the multifractal cross-correlation analysis technique, which provides information about the nonlinear effects in coupling of time series. We show that the considered network models are characterized by unique multifractal properties of the cross-correlation. In particular, it is possible to distinguish between Erdös-Rényi, Barabási-Albert, and Watts-Strogatz networks on the basis of fractal cross-correlation. Moreover, the analysis of protein contact networks reveals characteristics shared with both scale-free and small-world models.

RApid Temporal Survey (RATS) - II. Followup observations of four newly discovered short-period variables

NASA Astrophysics Data System (ADS)

Ramsay, Gavin; Napiwotzki, Ralf; Hakala, Pasi; Lehto, Harry

2006-09-01

The Rapid Temporal Survey (RATS) is a survey to detect objects whose optical intensity varies on time-scales of less than ~70 min. In our pilot data set taken with the Isaac Newton Telescope and the Wide Field Camera in 2003 November, we discovered nearly 50 new variable objects. Many of these varied on time-scales much longer than 1 h. However, only four objects showed a modulation on a time-scale of 1 h or less. This paper presents followup optical photometry and spectroscopy of these four objects. We find that RATJ0455 + 1305 is a pulsating (on a period of 374 s) subdwarf B star of the EC14026 type. We have modelled its spectrum and determine Teff = 29200 +/- 1900K and logg = 5.2 +/- 0.3 which locates it on the cool edge of the EC14026 instability strip. It has a modulation amplitude which is one of the highest of any known EC14026 star. Based on their spectra, photometric variability and their infrared colours, we find that RATJ0449 + 1756, J0455 + 1254 and J0807 + 1510 are likely to be SX Phe stars - dwarf δ Sct stars. Our results show that our observing strategy is a good method for finding rare pulsating stars.

Solar Spectral Irradiance Reconstruction over 9 Millennia from a Composite 14C and 10Be Series

NASA Astrophysics Data System (ADS)

Wu, C. J.; Usoskin, I. G.; Krivova, N.; Kovaltsov, G.; Solanki, S. K.

2017-12-01

The Sun is the main external energy source to the Earth and thus the knowledge of solar variability on different time scales is important for understanding the solar influence on the terrestrial atmosphere and climate. The overall energy input and its spectral distribution are described by the total (TSI) and spectral (SSI) solar irradiance, respectively. Direct measurements of the solar irradiance provide information on solar variability on the decadal and shorter time scales, while the sunspot number record covers four centuries. On yet longer time scales only indirect proxies can be used, such as the concentrations of the cosmogenic isotopes 10Be and 14C in terrestrial archives. These isotopes are produced in the terrestrial atmosphere by impinging cosmic rays, whose flux is modulated by solar activity. Therefore the isotope data retrieved from various natural archives around the globe show a very high degree of similarity reflecting changes in the solar activity. Nevertheless, significant short-term deviations can be observed due to the different geochemical production processes and local climatic conditions. We will present the newest TSI/SSI reconstruction over the last 9000 years based on a new consistent composite multi-isotope proxy series. The solar irradiance reconstruction reveals the global and robust pattern of solar variability in the past.

The role of environmental variables in structuring landscape-scale species distributions in seafloor habitats.

PubMed

Kraan, Casper; Aarts, Geert; Van der Meer, Jaap; Piersma, Theunis

2010-06-01

Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.

Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices

USGS Publications Warehouse

Ault, Toby R.; Schwartz, Mark D.; Zurita-Milla, Raul; Weltzin, Jake F.; Betancourt, Julio L.

2015-01-01

Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous United States. This dataset is derived from daily interpolated meteorological data, and the results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from 20.8 to 21.6 days decade21, while first bloom index trends are between20.4 and 21.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal time scales. Finally, there is some potential for successful subseasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

PubMed

Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

2017-10-27

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

Range-wide reproductive consequences of ocean climate variability for the seabird Cassin's Auklet.

PubMed

Wolf, Shaye G; Sydeman, William J; Hipfner, J Mark; Abraham, Christine L; Tershy, Bernie R; Croll, Donald A

2009-03-01

We examine how ocean climate variability influences the reproductive phenology and demography of the seabird Cassin's Auklet (Ptychoramphus aleuticus) across approximately 2500 km of its breeding range in the oceanographically dynamic California Current System along the west coast of North America. Specifically, we determine the extent to which ocean climate conditions and Cassin's Auklet timing of breeding and breeding success covary across populations in British Columbia, central California, and northern Mexico over six years (2000-2005) and test whether auklet timing of breeding and breeding success are similarly related to local and large-scale ocean climate indices across populations. Local ocean foraging environments ranged from seasonally variable, high-productivity environments in the north to aseasonal, low-productivity environments to the south, but covaried similarly due to the synchronizing effects of large-scale climate processes. Auklet timing of breeding in the southern population did not covary with populations to the north and was not significantly related to local oceanographic conditions, in contrast to northern populations, where timing of breeding appears to be influenced by oceanographic cues that signal peaks in prey availability. Annual breeding success covaried similarly across populations and was consistently related to local ocean climate conditions across this system. Overall, local ocean climate indices, particularly sea surface height, better explained timing of breeding and breeding success than a large-scale climate index by better representing heterogeneity in physical processes important to auklets and their prey. The significant, consistent relationships we detected between Cassin's Auklet breeding success and ocean climate conditions across widely spaced populations indicate that Cassin's Auklets are susceptible to climate change across the California Current System, especially by the strengthening of climate processes that synchronize oceanographic conditions. Auklet populations in the northern and central regions of this ecosystem may be more sensitive to changes in the timing and variability of ocean climate conditions since they appear to time breeding to take advantage of seasonal productivity peaks.

Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1

Multi-Scale Observation of Time-Variable Interactions of a Stream and its Valley Bottom During a Storm Event

NASA Astrophysics Data System (ADS)

Hixson, J.; Ward, A. S.; Schmadel, N.

2015-12-01

The exchange of water and solutes across the stream-hyporheic-riparian-hillslope continuum is controlled by the interaction of dynamic hydrological processes with the underlying geological setting. Our current understanding of exchange processes is primarily based on field observations collected during baseflow conditions, with few studies considering time-variable stream-aquifer interactions during storm events. We completed ten sets of four in-stream tracer slug injections during and after a large storm event in a headwater catchment at the H.J. Andrews Experimental Forest, Oregon. The injections were performed in three adjacent 50-meter study reaches, enabling comparison of spatial heterogeneity in transport processes. Reach-scale data demonstrate apparent trends with discharge in both transient storage and long-term storage (commonly "channel water balance"). Comparison of flowpath-scale observations from a network of monitoring wells to reach-scale observations showed that the advective timescale changed with discharge making it difficult to infer process from simple, reach-scale tracer studies. Overall, our results highlight the opportunities and challenges for interpretation of multi-scale solute tracer data along the stream-hyporheic-riparian-hillslope continuum.

Time-Frequency Analysis of Beach Bacteria Variations and its Implication for Recreational Water Quality Modeling

EPA Science Inventory

This paper explores the potential of time-frequency wavelet analysis in resolving beach bacteria concentration and possible explanatory variables across multiple time scales with temporal information still preserved. The wavelet scalograms of E. coli concentrations and the explan...

Antarctic lakes suggest millennial reorganizations of Southern Hemisphere atmospheric and oceanic circulation

PubMed Central

Hall, Brenda L.; Denton, George H.; Fountain, Andrew G.; Hendy, Chris H.; Henderson, Gideon M.

2010-01-01

The phasing of millennial-scale oscillations in Antarctica relative to those elsewhere in the world is important for discriminating among models for abrupt climate change, particularly those involving the Southern Ocean. However, records of millennial-scale variability from Antarctica dating to the last glacial maximum are rare and rely heavily on data from widely spaced ice cores, some of which show little variability through that time. Here, we present new data from closed-basin lakes in the Dry Valleys region of East Antarctica that show high-magnitude, high-frequency oscillations in surface level during the late Pleistocene synchronous with climate fluctuations elsewhere in the Southern Hemisphere. These data suggest a coherent Southern Hemisphere pattern of climate change on millennial time scales, at least in the Pacific sector, and indicate that any hypothesis concerning the origin of these events must account for synchronous changes in both high and temperate latitudes. PMID:21115838

Antarctic lakes suggest millennial reorganizations of Southern Hemisphere atmospheric and oceanic circulation.

PubMed

Hall, Brenda L; Denton, George H; Fountain, Andrew G; Hendy, Chris H; Henderson, Gideon M

2010-12-14

The phasing of millennial-scale oscillations in Antarctica relative to those elsewhere in the world is important for discriminating among models for abrupt climate change, particularly those involving the Southern Ocean. However, records of millennial-scale variability from Antarctica dating to the last glacial maximum are rare and rely heavily on data from widely spaced ice cores, some of which show little variability through that time. Here, we present new data from closed-basin lakes in the Dry Valleys region of East Antarctica that show high-magnitude, high-frequency oscillations in surface level during the late Pleistocene synchronous with climate fluctuations elsewhere in the Southern Hemisphere. These data suggest a coherent Southern Hemisphere pattern of climate change on millennial time scales, at least in the Pacific sector, and indicate that any hypothesis concerning the origin of these events must account for synchronous changes in both high and temperate latitudes.

Anomalous dispersion in correlated porous media: a coupled continuous time random walk approach

NASA Astrophysics Data System (ADS)

Comolli, Alessandro; Dentz, Marco

2017-09-01

We study the causes of anomalous dispersion in Darcy-scale porous media characterized by spatially heterogeneous hydraulic properties. Spatial variability in hydraulic conductivity leads to spatial variability in the flow properties through Darcy's law and thus impacts on solute and particle transport. We consider purely advective transport in heterogeneity scenarios characterized by broad distributions of heterogeneity length scales and point values. Particle transport is characterized in terms of the stochastic properties of equidistantly sampled Lagrangian velocities, which are determined by the flow and conductivity statistics. The persistence length scales of flow and transport velocities are imprinted in the spatial disorder and reflect the distribution of heterogeneity length scales. Particle transitions over the velocity length scales are kinematically coupled with the transition time through velocity. We show that the average particle motion follows a coupled continuous time random walk (CTRW), which is fully parameterized by the distribution of flow velocities and the medium geometry in terms of the heterogeneity length scales. The coupled CTRW provides a systematic framework for the investigation of the origins of anomalous dispersion in terms of heterogeneity correlation and the distribution of conductivity point values. We derive analytical expressions for the asymptotic scaling of the moments of the spatial particle distribution and first arrival time distribution (FATD), and perform numerical particle tracking simulations of the coupled CTRW to capture the full average transport behavior. Broad distributions of heterogeneity point values and lengths scales may lead to very similar dispersion behaviors in terms of the spatial variance. Their mechanisms, however are very different, which manifests in the distributions of particle positions and arrival times, which plays a central role for the prediction of the fate of dissolved substances in heterogeneous natural and engineered porous materials. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi

2017-04-01

The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Effect of Temperature on Heart Rate Variability in Neonatal ICU Patients With Hypoxic-Ischemic Encephalopathy.

PubMed

Massaro, An N; Campbell, Heather E; Metzler, Marina; Al-Shargabi, Tareq; Wang, Yunfei; du Plessis, Adre; Govindan, Rathinaswamy B

2017-04-01

To determine whether measures of heart rate variability are related to changes in temperature during rewarming after therapeutic hypothermia for hypoxic-ischemic encephalopathy. Prospective observational study. Level 4 neonatal ICU in a free-standing academic children's hospital. Forty-four infants with moderate to severe hypoxic-ischemic encephalopathy treated with therapeutic hypothermia. Continuous electrocardiogram data from 2 hours prior to rewarming through 2 hours after completion of rewarming (up to 10 hr) were analyzed. Median beat-to-beat interval and measures of heart rate variability were quantified including beat-to-beat interval SD, low and high frequency relative spectral power, detrended fluctuation analysis short and long α exponents (αS and αL), and root mean square short and long time scales. The relationships between heart rate variability measures and esophageal/axillary temperatures were evaluated. Heart rate variability measures low frequency, αS, and root mean square short and long time scales were negatively associated, whereas αL was positively associated, with temperature (p < 0.01). These findings signify an overall decrease in heart rate variability as temperature increased toward normothermia. Measures of heart rate variability are temperature dependent in the range of therapeutic hypothermia to normothermia. Core body temperature needs to be considered when evaluating heart rate variability metrics as potential physiologic biomarkers of illness severity in hypoxic-ischemic encephalopathy infants undergoing therapeutic hypothermia.

The role of SST variability in the simulation of the MJO

NASA Astrophysics Data System (ADS)

Stan, Cristiana

2017-12-01

The sensitivity of the Madden-Julian Oscillation to high-frequency variability (period 1-5 days) of sea surface temperature (SST) is investigated using numerical experiments with the super-parameterized Community Climate System Model. The findings of this study emphasize the importance of air-sea interactions in the simulation of the MJO, and stress the necessity of an accurate representation of ocean variability on short time scales. Eliminating 1-5-day variability of surface boundary forcing reduces the intraseasonal variability (ISV) of the tropics during the boreal winter. The ISV spectrum becomes close to the red noise background spectrum. The variability of atmospheric circulation shifts to longer time scales. In the absence of high-frequency variability of SST the MJO power gets confined to wavenumbers 1-2 and the magnitude of westward power associated with Rossby waves increases. The MJO convective activity propagating eastward from the Indian Ocean does not cross the Maritime Continent, and convection in the western Pacific Ocean is locally generated. In the Indian Ocean convection tends to follow the meridional propagation of SST anomalies. The response of the MJO to 1-5-day variability in the SST is through the charging and discharging mechanisms contributing to the atmospheric column moist static energy before and after peak MJO convection. Horizontal advection and surface fluxes show the largest sensitivity to SST perturbations.

Modelling solute dispersion in periodic heterogeneous porous media: Model benchmarking against intermediate scale experiments

NASA Astrophysics Data System (ADS)

Majdalani, Samer; Guinot, Vincent; Delenne, Carole; Gebran, Hicham

2018-06-01

This paper is devoted to theoretical and experimental investigations of solute dispersion in heterogeneous porous media. Dispersion in heterogenous porous media has been reported to be scale-dependent, a likely indication that the proposed dispersion models are incompletely formulated. A high quality experimental data set of breakthrough curves in periodic model heterogeneous porous media is presented. In contrast with most previously published experiments, the present experiments involve numerous replicates. This allows the statistical variability of experimental data to be accounted for. Several models are benchmarked against the data set: the Fickian-based advection-dispersion, mobile-immobile, multirate, multiple region advection dispersion models, and a newly proposed transport model based on pure advection. A salient property of the latter model is that its solutions exhibit a ballistic behaviour for small times, while tending to the Fickian behaviour for large time scales. Model performance is assessed using a novel objective function accounting for the statistical variability of the experimental data set, while putting equal emphasis on both small and large time scale behaviours. Besides being as accurate as the other models, the new purely advective model has the advantages that (i) it does not exhibit the undesirable effects associated with the usual Fickian operator (namely the infinite solute front propagation speed), and (ii) it allows dispersive transport to be simulated on every heterogeneity scale using scale-independent parameters.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

Simultaneous Ultraviolet Line and Continuum Variability Studies in Seyfert 1 Galaxies and Quasars

NASA Astrophysics Data System (ADS)

Honnappa, Vijayakumar; Prabhakar, Vedavvathi

Simultaneous Ultraviolet Line and Continuum Variability Studies in Seyfert 1 Galaxies and Quasars Vijayakumar H. Doddamani*and P. Vedavathi Department of Physics, Bangalore University, Bangalore-560056, *Corresponding author:drvkdmani@gmail.com, Abstract The line and continuum flux variability is a hallmark phenomenon of Seyfert 1 galaxies and quasars. Large amplitude luminosity variability is observed in AGNs from x-rays through radio waves over a wide-ranging timescales from minutes to years. The combinations of high luminosity and short variability time scales suggests, that the power of AGN is produced by a phenomena more efficient in terms of energy release per unit mass than ordinary stellar processes. The basic structure of AGNs thus developed based on the variability studies consists of a central super massive black hole surrounded by an accretion disk or more generally optically thick plasma radiating brightly at UV and soft X-ray wavelengths. The variability studies have been important tools of understanding the physics of the central regions of AGNs, which in general cannot be resolved with the existing or planned ground and space telescopes. Therefore, we have undertaken a study of the simultaneous ultraviolet line and continuum flux variability studies in MRK501, ESOB113-IG45 (also called as Fairall 9), MRK1506, MRK1095 V*GQCOM, PG1211+143, MRK205, PG1226+023 (also known as 3C273), PG1351+640, MRK 1383, MRK876 and QSO2251-178 as these objects have been repeatedly observed by IUE satellite over several years.. It is observed that Fairall 9, MRK 1095 and 3C273 exhibit the large amplitude variability (» 30 times) over the observed timescale, which spans several years. The remaining nine objects exhibit small amplitude (» 5 times) variability over the long time scale of observations. The highest amplitude variability is observed in Lya with a least in the MgII line. The amplitude of variability decreases in the order of Lya, CIV and Mg II, lines. These results suggest that the BLR is spatially stratified into different regions from the central compact nuclear engine. Keywords: Active galaxies, Seyfert galaxies, Quasars, Line and continuum, Variability, Supermassive black hole

Biological consequences of interaction of the climatic and event scales of variability in the Eastern Tropical Pacific. [Variations in fish populations

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

Walsh, J.J.

1976-01-01

Temporal changes of the Plymouth herring, Atlanto-Scandian herring, Norweigian cod, New York menhaden, Maine lobster, California sardine, anchovy, and red crab, and Japanese herring and sardine are considered in relation to oscillations of Peruvian anchovy and guano bird populations in response to variations of wind strength, of atmospheric and sea surface temperature anomalies, and of current speed for the Eastern Tropical Pacific. It is suggested that marine communities, either off Peru or throughout the ocean, respond in a similar manner to global oscillations at the climatic and El Nino scales by geographical relocation of their centers of abundance. It ismore » further suggested that these two longer scales of variability are minor perturbations of marine ecosystems in comparison with an interaction of overfishing and natural oscillations at the event scale of variability, i.e., that the failure of most of the world's clupeid fisheries may be linked to imposition of this additional stress and the local perturbations of the larval drift of an organism on a time scale of days to weeks.« less

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

NASA Astrophysics Data System (ADS)

Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.

2018-05-01

Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β = -1 and -3 at scales ≥ 500 km, while at scales ≤ 500 km they are typically near β ≈ -2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near -3. Within the tropics, however, the large-scale β for T is closer to -1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between -2 and -3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.

Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

NASA Astrophysics Data System (ADS)

Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

2010-03-01

The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect (temperature, dissolved oxygen in sediment and water) as well as the effect of microbial activities on chironomid larvae. Our results show that a multi-scale approach identifies patchy distribution, even when there is relative environmental homogeneity.

Variability of the raindrop size distribution at small spatial scales

NASA Astrophysics Data System (ADS)

Berne, A.; Jaffrain, J.

2010-12-01

Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.

On the area of accretion curtains from fast aperiodic time variability of the intermediate polar EX Hya

NASA Astrophysics Data System (ADS)

Semena, Andrey N.; Revnivtsev, Mikhail G.; Buckley, David A. H.; Kotze, Marissa M.; Khabibullin, Ildar I.; Breytenbach, Hannes; Gulbis, Amanda A. S.; Coppejans, Rocco; Potter, Stephen B.

2014-08-01

We present results of a study of the fast timing variability of the magnetic cataclysmic variable (mCV) EX Hya. It was previously shown that one may expect the rapid flux variability of mCVs to be smeared out at time-scales shorter than the cooling time of hot plasma in the post-shock region of the accretion curtain near the white dwarf (WD) surface. Estimates of the cooling time and the mass accretion rate, thus provide us with a tool to measure the density of the post-shock plasma and the cross-sectional area of the accretion funnel at the WD surface. We have probed the high frequencies in the aperiodic noise of one of the brightest mCV EX Hya with the help of optical telescopes, namely Southern African Large Telescope and the South African Astronomical Observatory 1.9 m telescope. We place upper limits on the plasma cooling time-scale τ < 0.3 s, on the fractional area of the accretion curtain footprint f < 1.6 × 10-4, and a lower limit on the specific mass accretion rate Ṁ/A>3 g s-1 cm-2. We show that measurements of accretion column footprints via eclipse mapping highly overestimate their areas. We deduce a value of Δr/r ≲ 10- 3 as an upper limit to the penetration depth of the accretion disc plasma at the boundary of the magnetosphere.

Scaling of the space-time correlation function of particle currents in a suspension of hard-sphere-like particles: exposing when the motion of particles is Brownian.

PubMed

van Megen, W; Martinez, V A; Bryant, G

2009-12-18

The current correlation function is determined from dynamic light scattering measurements of a suspension of particles with hard spherelike interactions. For suspensions in thermodynamic equilibrium we find scaling of the space and time variables of the current correlation function. This finding supports the notion that the movement of suspended particles can be described in terms of uncorrelated Brownian encounters. However, in the metastable fluid, at volume fractions above freezing, this scaling fails.

Holocene variability in the intensity of wind-gap upwelling in the tropical eastern Pacific

USGS Publications Warehouse

Toth, Lauren T.; Aronson, Richard B.; Cheng, Hai; Edwards, R. Lawrence

2015-01-01

Wind-driven upwelling in Pacific Panamá is a significant source of oceanographic variability in the tropical eastern Pacific. This upwelling system provides a critical teleconnection between the Atlantic and tropical Pacific that may impact climate variability on a global scale. Despite its importance to oceanographic circulation, ecology, and climate, little is known about the long-term stability of the Panamanian upwelling system or its interaction with climatic forcing on millennial time scales. Using a combination of radiocarbon and U-series dating of fossil corals collected in cores from five sites across Pacific Panamá, we reconstructed the local radiocarbon reservoir correction, ΔR, from ~6750 cal B.P. to present. Because the ΔR of shallow-water environments is elevated by upwelling, our data set represents a millennial-scale record of spatial and temporal variability of the Panamanian upwelling system. The general oceanographic gradient from relatively strong upwelling in the Gulf of Panamá to weak-to-absent upwelling in the Gulf of Chiriquí was present throughout our record; however, the intensity of upwelling in the Gulf of Panamá varied significantly through time. Our reconstructions suggest that upwelling in the Gulf of Panamá is weak at present; however, the middle Holocene was characterized by periods of enhanced upwelling, with the most intense upwelling occurring just after of a regional shutdown in the development of reefs at ~4100 cal B.P. Comparisons with regional climate proxies suggest that, whereas the Intertropical Convergence Zone is the primary control on modern upwelling in Pacific Panamá, the El Niño–Southern Oscillation drove the millennial-scale variability of upwelling during the Holocene.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages. PMID:29420548

A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables

NASA Astrophysics Data System (ADS)

Madonna, Erica; Ginsbourger, David; Martius, Olivia

2018-05-01

In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013

USGS Publications Warehouse

Driscoll, Jessica; Hay, Lauren E.; Bock, Andrew R.

2017-01-01

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.

Water-vapour variability within a convective boundary-layer assessed by large-eddy simulations and IHOP_2002 observations

NASA Astrophysics Data System (ADS)

Couvreux, F.; Guichard, F.; Redelsperger, J. L.; Kiemle, C.; Masson, V.; Lafore, J. P.; Flamant, C.

2005-10-01

This study presents a comprehensive analysis of the variability of water vapour in a growing convective boundary-layer (CBL) over land, highlighting the complex links between advection, convective activity and moisture heterogeneity in the boundary layer. A Large-eddy Simulation (LES) is designed, based on observations, and validated, using an independent data-set collected during the International H2O Project (IHOP 2002) fieldexperiment. Ample information about the moisture distribution in space and time, as well as other important CBL parameters are acquired by mesonet stations, balloon soundings, instruments on-board two aircraft and the DLR airborne water-vapour differential-absorption lidar. Because it can deliver two-dimensional cross-sections at high spatial resolution (140 m horizontal, 200 m vertical), the airborne lidar offers valuable insights of small-scale moisture-variability throughout the CBL. The LES is able to reproduce the development of the CBL in the morning and early afternoon, as assessed by comparisons of simulated mean profiles of key meteorological variables with sounding data. Simulated profiles of the variance of water-vapour mixing-ratio were found to be in good agreement with the lidar-derived counterparts. Finally, probability-density functions of potential temperature, vertical velocity and water-vapour mixing-ratio calculated from the LES show great consistency with those derived from aircraft in situ measurements in the middle of the CBL. Downdraughts entrained from above the CBL are governing the scale of moisture variability. Characteristic length-scales are found to be larger for water-vapour mixing-ratio than for temperature.The observed water-vapour variability exhibits contributions from different scales. The influence of the mesoscale (larger than LES domain size, i.e. 10 km) on the smaller-scale variability is assessed using LES and observations. The small-scale variability of water vapour is found to be important and to be driven by the dynamics of the CBL. Both lidar observations and LES evidence that dry downdraughts entrained from above the CBL are governing the scale of moisture variability. Characteristic length-scales are found to be larger for water-vapour mixing-ratio than for temperature and vertical velocity. In particular, intrusions of drier free-troposphere air from above the growing CBL impose a marked negative skewness on the water-vapour distribution within it, both as observed and in the simulation.

Mesoscale to Synoptic Scale Cloud Variability

NASA Technical Reports Server (NTRS)

Rossow, William B.

1998-01-01

The atmospheric circulation and its interaction with the oceanic circulation involve non-linear and non-local exchanges of energy and water over a very large range of space and time scales. These exchanges are revealed, in part, by the related variations of clouds, which occur on a similar range of scales as the atmospheric motions that produce them. Collection of comprehensive measurements of the properties of the atmosphere, clouds and surface allows for diagnosis of some of these exchanges. The use of a multi-satellite-network approach by the International Satellite Cloud Climatology Project (ISCCP) comes closest to providing complete coverage of the relevant range space and time scales over which the clouds, atmosphere and ocean vary. A nearly 15-yr dataset is now available that covers the range from 3 hr and 30 km to decade and planetary. This paper considers three topics: (1) cloud variations at the smallest scales and how they may influence radiation-cloud interactions, and (2) cloud variations at "moderate" scales and how they may cause natural climate variability, and (3) cloud variations at the largest scales and how they affect the climate. The emphasis in this discussion is on the more mature subject of cloud-radiation interactions. There is now a need to begin similar detailed diagnostic studies of water exchange processes.

Full-Scale Numerical Modeling of Turbulent Processes in the Earth's Ionosphere

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

Eliasson, B.; Stenflo, L.; Department of Physics, Linkoeping University, SE-581 83 Linkoeping

2008-10-15

We present a full-scale simulation study of ionospheric turbulence by means of a generalized Zakharov model based on the separation of variables into high-frequency and slow time scales. The model includes realistic length scales of the ionospheric profile and of the electromagnetic and electrostatic fields, and uses ionospheric plasma parameters relevant for high-latitude radio facilities such as Eiscat and HAARP. A nested grid numerical method has been developed to resolve the different length-scales, while avoiding severe restrictions on the time step. The simulation demonstrates the parametric decay of the ordinary mode into Langmuir and ion-acoustic waves, followed by a Langmuirmore » wave collapse and short-scale caviton formation, as observed in ionospheric heating experiments.« less

Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates

NASA Astrophysics Data System (ADS)

Mohanty, B.; Neelam, M.

2017-12-01

The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.

Time scale bias in erosion rates of glaciated landscapes

PubMed Central

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P.; Fischer, Woodward W.; Avouac, Jean-Philippe

2016-01-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time. PMID:27713925

Time scale bias in erosion rates of glaciated landscapes.

PubMed

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P; Fischer, Woodward W; Avouac, Jean-Philippe

2016-10-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time.

Optimal control of singularly perturbed nonlinear systems with state-variable inequality constraints

NASA Technical Reports Server (NTRS)

Calise, A. J.; Corban, J. E.

1990-01-01

The established necessary conditions for optimality in nonlinear control problems that involve state-variable inequality constraints are applied to a class of singularly perturbed systems. The distinguishing feature of this class of two-time-scale systems is a transformation of the state-variable inequality constraint, present in the full order problem, to a constraint involving states and controls in the reduced problem. It is shown that, when a state constraint is active in the reduced problem, the boundary layer problem can be of finite time in the stretched time variable. Thus, the usual requirement for asymptotic stability of the boundary layer system is not applicable, and cannot be used to construct approximate boundary layer solutions. Several alternative solution methods are explored and illustrated with simple examples.

The Use of Scale-Dependent Precision to Increase Forecast Accuracy in Earth System Modelling

NASA Astrophysics Data System (ADS)

Thornes, Tobias; Duben, Peter; Palmer, Tim

2016-04-01

At the current pace of development, it may be decades before the 'exa-scale' computers needed to resolve individual convective clouds in weather and climate models become available to forecasters, and such machines will incur very high power demands. But the resolution could be improved today by switching to more efficient, 'inexact' hardware with which variables can be represented in 'reduced precision'. Currently, all numbers in our models are represented as double-precision floating points - each requiring 64 bits of memory - to minimise rounding errors, regardless of spatial scale. Yet observational and modelling constraints mean that values of atmospheric variables are inevitably known less precisely on smaller scales, suggesting that this may be a waste of computer resources. More accurate forecasts might therefore be obtained by taking a scale-selective approach whereby the precision of variables is gradually decreased at smaller spatial scales to optimise the overall efficiency of the model. To study the effect of reducing precision to different levels on multiple spatial scales, we here introduce a new model atmosphere developed by extending the Lorenz '96 idealised system to encompass three tiers of variables - which represent large-, medium- and small-scale features - for the first time. In this chaotic but computationally tractable system, the 'true' state can be defined by explicitly resolving all three tiers. The abilities of low resolution (single-tier) double-precision models and similar-cost high resolution (two-tier) models in mixed-precision to produce accurate forecasts of this 'truth' are compared. The high resolution models outperform the low resolution ones even when small-scale variables are resolved in half-precision (16 bits). This suggests that using scale-dependent levels of precision in more complicated real-world Earth System models could allow forecasts to be made at higher resolution and with improved accuracy. If adopted, this new paradigm would represent a revolution in numerical modelling that could be of great benefit to the world.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

Non-stationary dynamics in the bouncing ball: A wavelet perspective

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

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in; Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding tomore » neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.« less

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Stellar Populations and Nearby Galaxies with the LSST

NASA Astrophysics Data System (ADS)

Saha, Abhijit; Olsen, K.; Monet, D. G.; LSST Stellar Populations Collaboration

2009-01-01

The LSST will produce a multi-color map and photometric object catalog of half the sky to r=27.6 (AB mag; 5-sigma). Time-space sampling of each field spanning ten years will allow variability, proper motion and parallax measurements for objects brighter than r=24.7. As part of providing an unprecedented map of the Galaxy, the accurate multi-band photometry will permit photometric parallaxes, chemical abundances and a handle on ages via colors at turn-off for main-sequence (MS) stars at all distances within the Galaxy as well as in the Magellanic Clouds, and dwarf satellites of the Milky Way. This will support comprehensive studies of star formation histories and chemical evolution for field stars. The structures of the Clouds and dwarf spheroidals will be traced with the MS stars, to equivalent surface densities fainter than 35 mag/square arc-second. With geometric parallax accuracy of 1 milli-arc-sec, comparable to HIPPARCOS but reaching more than 10 magnitudes fainter, a robust complete sample of solar neighborhood stars will be obtained. The LSST time sampling will identify and characterize variable stars of all types, from time scales of 1 hr to several years, a feast for variable star astrophysics. The combination of wide coverage, multi-band photometry, time sampling and parallax taken together will address several key problems: e.g. fine tuning the extragalactic distance scale by examining properties of RR Lyraes and Cepheids as a function of parent populations, extending the faint end of the galaxy luminosity function by discovering them using star count density enhancements on degree scales tracing, and indentifying inter-galactic stars through novae and Long Period Variables.

Correlation Lengths for Estimating the Large-Scale Carbon and Heat Content of the Southern Ocean

NASA Astrophysics Data System (ADS)

Mazloff, M. R.; Cornuelle, B. D.; Gille, S. T.; Verdy, A.

2018-02-01

The spatial correlation scales of oceanic dissolved inorganic carbon, heat content, and carbon and heat exchanges with the atmosphere are estimated from a realistic numerical simulation of the Southern Ocean. Biases in the model are assessed by comparing the simulated sea surface height and temperature scales to those derived from optimally interpolated satellite measurements. While these products do not resolve all ocean scales, they are representative of the climate scale variability we aim to estimate. Results show that constraining the carbon and heat inventory between 35°S and 70°S on time-scales longer than 90 days requires approximately 100 optimally spaced measurement platforms: approximately one platform every 20° longitude by 6° latitude. Carbon flux has slightly longer zonal scales, and requires a coverage of approximately 30° by 6°. Heat flux has much longer scales, and thus a platform distribution of approximately 90° by 10° would be sufficient. Fluxes, however, have significant subseasonal variability. For all fields, and especially fluxes, sustained measurements in time are required to prevent aliasing of the eddy signals into the longer climate scale signals. Our results imply a minimum of 100 biogeochemical-Argo floats are required to monitor the Southern Ocean carbon and heat content and air-sea exchanges on time-scales longer than 90 days. However, an estimate of formal mapping error using the current Argo array implies that in practice even an array of 600 floats (a nominal float density of about 1 every 7° longitude by 3° latitude) will result in nonnegligible uncertainty in estimating climate signals.

Identifying Changes of Complex Flood Dynamics with Recurrence Analysis

NASA Astrophysics Data System (ADS)

Wendi, D.; Merz, B.; Marwan, N.

2016-12-01

Temporal changes in flood hazard system are known to be difficult to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. Moreover hydrological time series (i.e. discharge) are often subject to measurement errors, such as rating curve error especially in the case of extremes where observation are actually derived through extrapolation. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. Sensitivity of the common measurement errors and noise on recurrence analysis will also be analyzed and evaluated against conventional methods. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic to certain flood events.

Effect of small versus large clusters of fish school on the yield of a purse-seine small pelagic fishery including a marine protected area.

PubMed

Hieu, Nguyen Trong; Brochier, Timothée; Tri, Nguyen-Huu; Auger, Pierre; Brehmer, Patrice

2014-09-01

We consider a fishery model with two sites: (1) a marine protected area (MPA) where fishing is prohibited and (2) an area where the fish population is harvested. We assume that fish can migrate from MPA to fishing area at a very fast time scale and fish spatial organisation can change from small to large clusters of school at a fast time scale. The growth of the fish population and the catch are assumed to occur at a slow time scale. The complete model is a system of five ordinary differential equations with three time scales. We take advantage of the time scales using aggregation of variables methods to derive a reduced model governing the total fish density and fishing effort at the slow time scale. We analyze this aggregated model and show that under some conditions, there exists an equilibrium corresponding to a sustainable fishery. Our results suggest that in small pelagic fisheries the yield is maximum for a fish population distributed among both small and large clusters of school.

Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...

The Geometric Phase of Stock Trading

PubMed Central

2016-01-01

Geometric phases describe how in a continuous-time dynamical system the displacement of a variable (called phase variable) can be related to other variables (shape variables) undergoing a cyclic motion, according to an area rule. The aim of this paper is to show that geometric phases can exist also for discrete-time systems, and even when the cycles in shape space have zero area. A context in which this principle can be applied is stock trading. A zero-area cycle in shape space represents the type of trading operations normally carried out by high-frequency traders (entering and exiting a position on a fast time-scale), while the phase variable represents the cash balance of a trader. Under the assumption that trading impacts stock prices, even zero-area cyclic trading operations can induce geometric phases, i.e., profits or losses, without affecting the stock quote. PMID:27556642

Evaluating the uncertainty of predicting future climate time series at the hourly time scale

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2011-12-01

A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

Short time-scale optical variability properties of the largest AGN sample observed with Kepler/K2

NASA Astrophysics Data System (ADS)

Aranzana, E.; Körding, E.; Uttley, P.; Scaringi, S.; Bloemen, S.

2018-05-01

We present the first short time-scale (˜hours to days) optical variability study of a large sample of active galactic nuclei (AGNs) observed with the Kepler/K2 mission. The sample contains 252 AGN observed over four campaigns with ˜30 min cadence selected from the Million Quasar Catalogue with R magnitude <19. We performed time series analysis to determine their variability properties by means of the power spectral densities (PSDs) and applied Monte Carlo techniques to find the best model parameters that fit the observed power spectra. A power-law model is sufficient to describe all the PSDs of our sample. A variety of power-law slopes were found indicating that there is not a universal slope for all AGNs. We find that the rest-frame amplitude variability in the frequency range of 6 × 10-6-10-4 Hz varies from 1to10 per cent with an average of 1.7 per cent. We explore correlations between the variability amplitude and key parameters of the AGN, finding a significant correlation of rest-frame short-term variability amplitude with redshift. We attribute this effect to the known `bluer when brighter' variability of quasars combined with the fixed bandpass of Kepler data. This study also enables us to distinguish between Seyferts and blazars and confirm AGN candidates. For our study, we have compared results obtained from light curves extracted using different aperture sizes and with and without detrending. We find that limited detrending of the optimal photometric precision light curve is the best approach, although some systematic effects still remain present.

X-ray flux variability of active galactic nuclei observed using NuSTAR

NASA Astrophysics Data System (ADS)

Rani, Priyanka; Stalin, C. S.; Rakshit, Suvendu

2017-04-01

We present results of a systematic study of flux variability on hourly time-scales in a large sample of active galactic nuclei (AGN) in the 3-79 keV band using data from Nuclear Spectroscopic Telescope Array. Our sample consists of four BL Lac objects (BL Lacs), three flat spectrum radio quasars (FSRQs) 24 Seyfert 1, 42 Seyfert 2 and eight narrow line Seyfert 1 (NLSy1) galaxies. We find that in the 3-79 keV band, about 65 per cent of the sources in our sample show significant variations on hourly time-scales. Using the Mann-Whitney U-test and the Kolmogorov-Smirnov test, we find no difference in the variability behaviour between Seyfert 1 and 2 galaxies. The blazar sources (FSRQs and BL Lacs) in our sample are more variable than Seyfert galaxies that include Seyfert 1 and Seyfert 2 in the soft (3-10 keV), hard (10-79 keV) and total (3-79 keV) bands. NLSy1 galaxies show the highest duty cycle of variability (87 per cent), followed by BL Lacs (82 per cent), Seyfert galaxies (56 per cent) and FSRQs (23 per cent). We obtained flux doubling/halving time in the hard X-ray band less than 10 min in 11 sources. The flux variations between the hard and soft bands in all the sources in our sample are consistent with zero lag.

Comparing Building and Neighborhood-Scale Variability of CO₂ and O₃ to Inform Deployment Considerations for Low-Cost Sensor System Use.

PubMed

Collier-Oxandale, Ashley; Coffey, Evan; Thorson, Jacob; Johnston, Jill; Hannigan, Michael

2018-04-26

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.

The QBO Impact on Stratospheric Composition as Revealed by the MERRA-2 GMI Simulation and NASA Satellite Observations

NASA Astrophysics Data System (ADS)

Oman, L.; Strahan, S. E.

2017-12-01

The Quasi-Biennial Oscillation (QBO) is the dominant mode of variability in the tropical stratosphere on interannual time scales. It has been shown to impact both stratospheric dynamics and important trace gas constituent distributions. The QBO timing with respect to the seasonal cycle in each hemisphere is significant in determining its impact on up to decadal scale variability. The composition response to the QBO is examined using the new MERRA-2 GMI "Replay" simulation, an atmospheric composition community resource, run at the native MERRA-2 approximately ½° horizontal resolution on the cubed sphere. MERRA-2 GMI is driven by the online use of key MERRA-2 meteorological quantities (i.e. U, V, T, and P) with all other variables calculated in response to those and boundary condition forcings from 1980-2016. The simulation combined with NASA's UARS and Aura satellite measurements have allowed us to quantify the impact of the QBO on stratospheric composition in more detail than was ever possible before. Revealing preferential pathways and transport timings necessary in understanding the QBO impact on composition throughout the stratosphere.

TEMPORAL VARIABILITY MEASUREMENT OF SPECIFIC VOLATILE ORGANIC COMPOUNDS

EPA Science Inventory

Methodology was developed to determine unambiguously trace levels of volatile organic compounds as they vary in concentration over a variety of time scales. his capability is important because volatile organic compounds (VOCs) are usually measure by time-integrative techniques th...

A multiple-time-scale turbulence model based on variable partitioning of turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1988-01-01

The paper presents a multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method. Consideration is given to a class of turbulent boundary layer flows and of separated and/or swirling elliptic turbulent flows. For the separated and/or swirling turbulent flows, the present turbulence model yielded significantly improved computational results over those obtained with the standard k-epsilon turbulence model.

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Travis, James E.

2013-01-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

NASA Astrophysics Data System (ADS)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Macroweather Predictions and Climate Projections using Scaling and Historical Observations

NASA Astrophysics Data System (ADS)

Hébert, R.; Lovejoy, S.; Del Rio Amador, L.

2017-12-01

There are two fundamental time scales that are pertinent to decadal forecasts and multidecadal projections. The first is the lifetime of planetary scale structures, about 10 days (equal to the deterministic predictability limit), and the second is - in the anthropocene - the scale at which the forced anthropogenic variability exceeds the internal variability (around 16 - 18 years). These two time scales define three regimes of variability: weather, macroweather and climate that are respectively characterized by increasing, decreasing and then increasing varibility with scale.We discuss how macroweather temperature variability can be skilfully predicted to its theoretical stochastic predictability limits by exploiting its long-range memory with the Stochastic Seasonal and Interannual Prediction System (StocSIPS). At multi-decadal timescales, the temperature response to forcing is approximately linear and this can be exploited to make projections with a Green's function, or Climate Response Function (CRF). To make the problem tractable, we exploit the temporal scaling symmetry and restrict our attention to global mean forcing and temperature response using a scaling CRF characterized by the scaling exponent H and an inner scale of linearity τ. An aerosol linear scaling factor α and a non-linear volcanic damping exponent ν were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference using historical data and these allow us to analytically calculate a median (and likely 66% range) for the transient climate response, and for the equilibrium climate sensitivity: 1.6K ([1.5,1.8]K) and 2.4K ([1.9,3.4]K) respectively. Aerosol forcing typically has large uncertainty and we find a modern (2005) forcing very likely range (90%) of [-1.0, -0.3] Wm-2 with median at -0.7 Wm-2. Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to Representative Concentration Pathway (RCP) 2.6 for which the probability to remain under 1.5 K is 48%. RCP 4.5 and RCP 8.5-like futures overshoot with very high probability. This underscores that over the next century, the state of the environment will be strongly influenced by past, present and future economical policies.

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

PubMed

King, Adam C; Newell, Karl M

2015-10-01

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

Revisiting a possible relationship between solar activity and Earth rotation variability

NASA Astrophysics Data System (ADS)

Abarca del Rio, R.; Gambis, D.

2011-10-01

A variety of studies have searched to establish a possible relationship between the solar activity and earth variations (Danjon, 1958-1962; Challinor, 1971; Currie, 1980, Gambis, 1990). We are revisiting previous studies (Bourget et al, 1992, Abarca del Rio et al, 2003, Marris et al, 2004) concerning the possible relationship between solar activity variability and length of day (LOD) variations at decadal time scales. Assuming that changes in AAM for the entire atmosphere are accompanied by equal, but opposite, changes in the angular momentum of the earth it is possible to infer changes in LOD from global AAM time series, through the relation : delta (LOD) (ms) = 1.68 10^29 delta(AAM) (kgm2/s) (Rosen and Salstein, 1983), where δ(LOD) is given in milliseconds. Given the close relationship at seasonal to interannual time's scales between LOD and the Atmospheric Angular Momentum (AAM) (see Abarca del Rio et al., 2003) it is possible to infer from century long atmospheric simulations what may have been the variability in the associated LOD variability throughout the last century. In the absence of a homogeneous century long LOD time series, we take advantage of the recent atmospheric reanalyzes extending since 1871 (Compo, Whitaker and Sardeshmukh, 2006). The atmospheric data (winds) of these reanalyzes allow computing AAM up to the top of the atmosphere; though here only troposphere data (up to 100 hPa) was taken into account.

Coupled hydrological and geochemical process evolution at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Troch, P. A. A.

2015-12-01

Predictions of hydrologic and biogeochemical responses to natural and anthropogenic forcing at the landscape scale are highly uncertain due to the effects of heterogeneity on the scaling of reaction, flow and transport phenomena. The physical, chemical and biological structures and processes controlling reaction, flow and transport in natural landscapes interact at multiple space and time scales and are difficult to quantify. The current paradigm of hydrological and geochemical theory is that process descriptions derived from observations at small scales in controlled systems can be applied to predict system response at much larger scales, as long as some 'equivalent' or 'effective' values of the scale-dependent parameters can be identified. Furthermore, natural systems evolve in time in a way that is hard to observe in short-run laboratory experiments or in natural landscapes with unknown initial conditions and time-variant forcing. The spatial structure of flow pathways along hillslopes determines the rate, extent and distribution of geochemical reactions (and biological colonization) that drive weathering, the transport and precipitation of solutes and sediments, and the further evolution of soil structure. The resulting evolution of structures and processes, in turn, produces spatiotemporal variability of hydrological states and flow pathways. There is thus a need for experimental research to improve our understanding of hydrology-biogeochemistry interactions and feedbacks at appropriate spatial scales larger than laboratory soil column experiments. Such research is complicated in real-world settings because of poorly constrained impacts of initial conditions, climate variability, ecosystems dynamics, and geomorphic evolution. The Landscape Evolution Observatory (LEO) at Biosphere 2 offers a unique research facility that allows real-time observations of incipient hydrologic and biogeochemical response under well-constrained initial conditions and climate forcing. The LEO allows to close the water, carbon and energy budgets at hillslope scales, thereby enabling elucidation of the tight coupling between the time water spends along subsurface flow paths and geochemical weathering reactions, including the feedbacks between flow and pedogenesis.

Photometry of the three eclipsing novalike variables EC 21178-5417, GS Pav and V345 Pav

NASA Astrophysics Data System (ADS)

Bruch, Albert

2017-10-01

As part of a project to better characterize comparatively bright, yet little studied cataclysmic variables time resolved photometry of the three eclipsing novalike variables EC 21178-5417, GS Pav und V345 Pav is presented. Previously known orbital periods are significantly improved and long-term ephemeris are derived. Variations of eclipse profiles, occurring on time scales of days to weeks, are analyzed. Out of eclipse the light curves are characterized by low scale flickering superposed on more gradual variations with amplitudes limited to a few tenths of a magnitude and profiles which at least in EC 21178-5417 and GS Pav roughly follow the same pattern in all observed cycles. Additionally, signs for variations on the time scale of some tens of minutes are seen in GS Pav, most clearly in two subsequent nights when in the first of these a signal with a period of 15.7 min was observed over several hours. In the second night variations with twice this period were seen. While no additional insight could be gained on quasi periodic oscillations (QPOs) and dwarf nova oscillations in EC 21178-5417, previously detected by Warner et al. (2003), and while such oscillations could not be found in V345 Pav, stacked power spectra of GS Pav clearly reveal the presence of QPOs over time intervals of several hours with periods varying between 200 s and 500 s in that system.

X-ray spectra and time variability of active galactic nuclei

NASA Technical Reports Server (NTRS)

Mushotzky, R. F.

1984-01-01

The X-ray spectra of broad line active galactic nuclei (AGN) of all types (Seyfert I's, NELG's, broadline radio galaxies) are well fit by a power law in the .5 to 100 keV band of man energy slope alpha = .68 + or - .15. There is, as yet, no strong evidence for time variability of this slope in a given object. The constraints that this places on simple models of the central energy source are discussed. BL Lac objects have quite different X-ray spectral properties and show pronounced X-ray spectral variability. On time scales longer than 12 hours most radio quiet AGN do not show strong, delta I/I .5, variability. The probability of variability of these AGN seems to be inversely related to their luminosity. However characteristics timescales for variability have not been measured for many objects. This general lack of variability may imply that most AGN are well below the Eddington limit. Radio bright AGN tend to be more variable than radio quiet AGN on long, tau approx 6 month, timescales.

Using New Theory and Experimental Methods to Understand the Relative Controls of Storage, Antecedent Conditions and Precipitation Intensity on Transit Time Distributions through a Sloping Soil Lysimeter

NASA Astrophysics Data System (ADS)

Kim, M.; Pangle, L. A.; Cardoso, C.; Lora, M.; Wang, Y.; Harman, C. J.; Troch, P. A. A.

2014-12-01

Transit time distributions (TTD) are an efficient way of characterizing transport through the complex flow dynamics of a hydrologic system, and can serve as a basis for spatially-integrated solute transport modeling. Recently there has been progress in the development of a theory of time-variable TTDs that captures the effect of temporal variability in the timing of fluxes as well as changes in flow pathways. Furthermore, a new formulation of this theory allows the essential transport properties of a system to be parameterized by a physically meaningful time-variable probability distribution, the Ω function. This distribution determines how the age distribution of water in storage is sampled by the outflow. The form of the Ω function varies if the flow pathways change, but is not determined by the timing of fluxes (unlike the TTD). In this study, we use this theory to characterize transport by transient flows through a homogeneously packed 1 m3 sloping soil lysimeter. The transit time distribution associated with each of four irrigation periods (repeated daily for 24 days) are compared to examine the significance of changes in the Ω function due to variations in total storage, antecedent conditions, and precipitation intensity. We observe both the time-variable TTD and the Ω function experimentally by applying the PERTH method (Harman and Kim, 2014, GRL, 41, 1567-1575). The method allows us to observe multiple overlapping time-variable TTD in controlled experiments using only two conservative tracers. We hypothesize that both the TTD and the Ω function will vary in time, even in this small scale, because water will take different flow pathways depending on the initial state of the lysimeter and irrigation intensity. However, based on primarily modeling, we conjecture that major variability in the Ω function will be limited to a period during and immediately after each irrigation. We anticipate the Ω function is almost time-invariant (or scales simply with total storage) during the recession period because flow pathways are stable during this period. This is one of the first experimental studies of this type, and the results offer insights into solute transport in transient, variably-saturated systems.

Multiscaling for systems with a broad continuum of characteristic lengths and times: Structural transitions in nanocomposites.

PubMed

Pankavich, S; Ortoleva, P

2010-06-01

The multiscale approach to N-body systems is generalized to address the broad continuum of long time and length scales associated with collective behaviors. A technique is developed based on the concept of an uncountable set of time variables and of order parameters (OPs) specifying major features of the system. We adopt this perspective as a natural extension of the commonly used discrete set of time scales and OPs which is practical when only a few, widely separated scales exist. The existence of a gap in the spectrum of time scales for such a system (under quasiequilibrium conditions) is used to introduce a continuous scaling and perform a multiscale analysis of the Liouville equation. A functional-differential Smoluchowski equation is derived for the stochastic dynamics of the continuum of Fourier component OPs. A continuum of spatially nonlocal Langevin equations for the OPs is also derived. The theory is demonstrated via the analysis of structural transitions in a composite material, as occurs for viral capsids and molecular circuits.

Predicting redox conditions in groundwater at a regional scale

USGS Publications Warehouse

Tesoriero, Anthony J.; Terziotti, Silvia; Abrams, Daniel B.

2015-01-01

Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

Flow and residence times of dynamic river bank storage and sinuosity-driven hyporheic exchange

USGS Publications Warehouse

Gomez-Velez, J.D.; Wilson, J.L.; Cardenas, M.B.; Harvey, Judson

2017-01-01

Hydrologic exchange fluxes (HEFs) vary significantly along river corridors due to spatiotemporal changes in discharge and geomorphology. This variability results in the emergence of biogeochemical hot-spots and hot-moments that ultimately control solute and energy transport and ecosystem services from the local to the watershed scales. In this work, we use a reduced-order model to gain mechanistic understanding of river bank storage and sinuosity-driven hyporheic exchange induced by transient river discharge. This is the first time that a systematic analysis of both processes is presented and serves as an initial step to propose parsimonious, physics-based models for better predictions of water quality at the large watershed scale. The effects of channel sinuosity, alluvial valley slope, hydraulic conductivity, and river stage forcing intensity and duration are encapsulated in dimensionless variables that can be easily estimated or constrained. We find that the importance of perturbations in the hyporheic zone's flux, residence times, and geometry is mainly explained by two-dimensionless variables representing the ratio of the hydraulic time constant of the aquifer and the duration of the event (Γd) and the importance of the ambient groundwater flow ( ). Our model additionally shows that even systems with small sensitivity, resulting in small changes in the hyporheic zone extent, are characterized by highly variable exchange fluxes and residence times. These findings highlight the importance of including dynamic changes in hyporheic zones for typical HEF models such as the transient storage model.

A precursive study of the time-domain survey of the Galactic Anti-center using the Nanshan 1-meter telescope with variable stars detected

NASA Astrophysics Data System (ADS)

Ma, Shu-Guo; Esamdin, Ali; Ma, Lu; Niu, Hu-Biao; Fu, Jian-Ning; Zhang, Yu; Liu, Jin-Zhong; Yang, Tao-Zhi; Song, Fang-Fang; Pu, Guang-Xin

2018-04-01

Following the LAMOST Spectroscopic Survey and the Xuyi's Photometric Survey of the Galactic Anti-center, we plan to carry out a time-domain survey of the Galactic Anti-center (TDS-GAC) to study variable stars by using the Nanshan 1-meter telescope. Before the beginning of TDS-GAC, a precursive sky survey (PSS) has been executed. The goal of the PSS is to optimize the observation strategy of TDS-GAC and to detect some strong transient events, as well as to find some short time-scale variable stars of different types. By observing a discontinuous sky area of 15.03 deg2 with the standard Johnson-Cousin-Bessel V filter, 48 variable stars are found and the time series are analyzed. Based on the behaviors of the light curves, 28 eclipsing binary stars, 10 RR Lyraes, 3 periodic pulsating variables of other types have been classified. The rest 7 variables stay unclassified with deficient data. In addition, the observation strategy of TD-GAC is described, and the pipeline of data reduction is tested.

The frequency response of a coupled ice sheet-ice shelf-ocean system to climate forcing variability

NASA Astrophysics Data System (ADS)

Goldberg, D.; Snow, K.; Jordan, J. R.; Holland, P.; Arthern, R. J.

2017-12-01

Changes at the West Antarctic ice-ocean boundary in recent decades has triggered significant increases in the regions contribution to global sea-level rise, coincident with large scale, and in some cases potentially unstable, grounding line retreat. Much of the induced change is thought to be driven by fluctuations in the oceanic heat available at the ice-ocean boundary, transported on-shelf via warm Circumpolar Deep Water (CDW). However, the processes in which ocean heat drives ice-sheet loss remains poorly understood, with observational studies routinely hindered by the extreme environment notorious to the Antarctic region. In this study we apply a novel synchronous coupled ice-ocean model, developed within the MITgcm, and are thus able to provide detailed insight into the impacts of short time scale (interannual to decadal) climate variability and feedbacks within the ice-ocean system. Feedbacks and response are assessed in an idealised ice-sheet/ocean-cavity configuration in which the far field ocean condition is adjusted to emulate periodic climate variability patterns. We reveal a non-linear response of the ice-sheet to periodic variations in thermocline depth. These non-linearities illustrate the heightened sensitivity of fast flowing ice-shelves to periodic perturbations in heat fluxes occurring at interannual and decadal time scales. The results thus highlight how small perturbations in variable climate forcing, like that of ENSO, may trigger large changes in ice-sheet response.

The Role of Fractality in Perceptual Learning: Exploration in Dynamic Touch

ERIC Educational Resources Information Center

Stephen, Damian G.; Arzamarski, Ryan; Michaels, Claire F.

2010-01-01

Perceptual systems must learn to explore and to use the resulting information to hone performance. Optimal performance depends on using information available at many time scales, from the near instantaneous values of variables underlying perception (i.e., detection), to longer term information about appropriate scaling (i.e., calibration), to yet…

Variable X-Ray Absorption in the Mini-BAL QSO PG 1126-041

NASA Technical Reports Server (NTRS)

Giustini, M.; Cappi, M.; Chartas, G.; Dadina, M.; Eracleous, M.; Ponti, G.; Proga, D.; Tombesi, F.; Vignali, C.; Palumbo, G. G. C.

2011-01-01

Context. X-ray studies of AGN with powerful nuclear winds are important to constrain the physics of the inner accretion/ejection flow around SMBH, and to understand the impact of such winds on the AGN environment. Aims. Our main scientific goal is to constrain the properties of a variable outflowing absorber that is thought to be launched near the SMBH of the mini-BAL QSO PG 1126-041 using a multi-epoch observational campaign performed with XMM-Newton. Methods. We performed temporally resolved X-ray spectroscopy and simultaneous UV and X-ray photometry on the most complete set of observations and on the deepest X-ray exposure of a mini-BAL QSO to date. Results. We found complex X-ray spectral variability on time scales of both months and hours, best reproduced by means of variable massive ionized absorbers along the line of sight. As a consequence, the observed optical-to-X-ray spectral index is found to be variable with time. In the highest signal-to-noise observation we detected highly ionized X-ray absorbing material outflowing much faster (u(sub X) approx. 16 500 km/s) than the UV absorbing one (u(sub uv) approx. 5,000 km/s). This highly ionized absorber is found to be variable on very short (a few kiloseconds) time scales. Conclusions. Our findings are qualitatively consistent with line driven accretion disk winds scenarios. Our observations have opened the time-resolved X-ray spectral analysis field for mini-BAL QSOs; only with future deep studies will we be able to map the dynamics of the inner flow and understand the physics of AGN winds and their impact on the environment.

The Response of Ice Sheets to Climate Variability

NASA Astrophysics Data System (ADS)

Snow, K.; Goldberg, D. N.; Holland, P. R.; Jordan, J. R.; Arthern, R. J.; Jenkins, A.

2017-12-01

West Antarctic Ice Sheet loss is a significant contributor to sea level rise. While the ice loss is thought to be triggered by fluctuations in oceanic heat at the ice shelf bases, ice sheet response to ocean variability remains poorly understood. Using a synchronously coupled ice-ocean model permitting grounding line migration, this study evaluates the response of an ice sheet to periodic variations in ocean forcing. Resulting oscillations in grounded ice volume amplitude is shown to grow as a nonlinear function of ocean forcing period. This implies that slower oscillations in climatic forcing are disproportionately important to ice sheets. The ice shelf residence time offers a critical time scale, above which the ice response amplitude is a linear function of ocean forcing period and below which it is quadratic. These results highlight the sensitivity of West Antarctic ice streams to perturbations in heat fluxes occurring at decadal time scales.

A global perspective on Glacial- to Interglacial variability change

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2017-04-01

Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

Short-term rainfall: its scaling properties over Portugal

NASA Astrophysics Data System (ADS)

de Lima, M. Isabel P.

2010-05-01

The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.

Brazilian infant motor and cognitive development: Longitudinal influence of risk factors.

PubMed

Pereira, Keila Rg; Valentini, Nadia C; Saccani, Raquel

2016-12-01

Infant developmental delays have been associated with several risk factors, such as familial environmental, individual and demographic characteristics. The goal of this study was to longitudinally investigate the effects of maternal knowledge and practices, home environment and biological factors on infant motor and cognitive outcomes. This was a prospective cohort study with a sample of 49 infants from Southern Brazil. The infants were assessed three times over 4 months using the Alberta Infant Motor Scale and the Bayley Scale of Infant Development (Mental Development Scale). Parents completed the Daily Activities Scale of Infants, the Affordances in The Home Environment for Motor Development - Infant Scale, the Knowledge of Infant Development Inventory and a demographic questionnaire. Generalized estimating equation with Bonferroni method as the follow-up test and Spearman correlation and multivariate linear backward regression were used. Cognitive and motor scores were strongly associated longitudinally and increased over time. Associations between the home affordances, parental practices and knowledge, and motor and cognitive development over time were observed. This relationship explained more variability in motor and cognitive scores compared with biological factors. Variability in motor and cognitive development is better explained by environment and parental knowledge and practice. The investigation of factors associated with infant development allows the identification of infants at risk and the implementation of educational programs and parental training to minimize the effects of developmental delay. © 2016 Japan Pediatric Society.

Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2016-04-01

Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i). (iii) Dominant non-stationary patterns are recognized as independent complex patterns that can be used to represent the space and time amplitude and phase propagations. We present the results of CICA on simulated and real cases e.g., for quantifying the impact of large-scale ocean-atmosphere interaction on global mass changes. Forootan (PhD-2014) Statistical signal decomposition techniques for analyzing time-variable satellite gravimetry data, PhD Thesis, University of Bonn, http://hss.ulb.uni-bonn.de/2014/3766/3766.htm Forootan and Kusche (JoG-2012) Separation of global time-variable gravity signals into maximally independent components, Journal of Geodesy 86 (7), 477-497, doi: 10.1007/s00190-011-0532-5

Wavelet analysis and scaling properties of time series

NASA Astrophysics Data System (ADS)

Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.

2005-10-01

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.

Implementation Strategies for Large-Scale Transport Simulations Using Time Domain Particle Tracking

NASA Astrophysics Data System (ADS)

Painter, S.; Cvetkovic, V.; Mancillas, J.; Selroos, J.

2008-12-01

Time domain particle tracking is an emerging alternative to the conventional random walk particle tracking algorithm. With time domain particle tracking, particles are moved from node to node on one-dimensional pathways defined by streamlines of the groundwater flow field or by discrete subsurface features. The time to complete each deterministic segment is sampled from residence time distributions that include the effects of advection, longitudinal dispersion, a variety of kinetically controlled retention (sorption) processes, linear transformation, and temporal changes in groundwater velocities and sorption parameters. The simulation results in a set of arrival times at a monitoring location that can be post-processed with a kernel method to construct mass discharge (breakthrough) versus time. Implementation strategies differ for discrete flow (fractured media) systems and continuous porous media systems. The implementation strategy also depends on the scale at which hydraulic property heterogeneity is represented in the supporting flow model. For flow models that explicitly represent discrete features (e.g., discrete fracture networks), the sampling of residence times along segments is conceptually straightforward. For continuous porous media, such sampling needs to be related to the Lagrangian velocity field. Analytical or semi-analytical methods may be used to approximate the Lagrangian segment velocity distributions in aquifers with low-to-moderate variability, thereby capturing transport effects of subgrid velocity variability. If variability in hydraulic properties is large, however, Lagrangian velocity distributions are difficult to characterize and numerical simulations are required; in particular, numerical simulations are likely to be required for estimating the velocity integral scale as a basis for advective segment distributions. Aquifers with evolving heterogeneity scales present additional challenges. Large-scale simulations of radionuclide transport at two potential repository sites for high-level radioactive waste will be used to demonstrate the potential of the method. The simulations considered approximately 1000 source locations, multiple radionuclides with contrasting sorption properties, and abrupt changes in groundwater velocity associated with future glacial scenarios. Transport pathways linking the source locations to the accessible environment were extracted from discrete feature flow models that include detailed representations of the repository construction (tunnels, shafts, and emplacement boreholes) embedded in stochastically generated fracture networks. Acknowledgment The authors are grateful to SwRI Advisory Committee for Research, the Swedish Nuclear Fuel and Waste Management Company, and Posiva Oy for financial support.

An investigation of the photometric variability of confirmed and candidate Galactic Be stars using ASAS-3 data

NASA Astrophysics Data System (ADS)

Bernhard, Klaus; Otero, Sebastián; Hümmerich, Stefan; Kaltcheva, Nadejda; Paunzen, Ernst; Bohlsen, Terry

2018-05-01

We present an investigation of a large sample of confirmed (N=233) and candidate (N=54) Galactic classical Be stars (mean V magnitude range of 6.4 to 12.6 mag), with the main aim of characterizing their photometric variability. Our sample stars were preselected among early-type variables using light curve morphology criteria. Spectroscopic information was gleaned from the literature, and archival and newly-acquired spectra. Photometric variability was analyzed using archival ASAS-3 time series data. To enable a comparison of results, we have largely adopted the methodology of Labadie-Bartz et al. (2017), who carried out a similar investigation based on KELT data. Complex photometric variations were established in most stars: outbursts on different time-scales (in 73±5 % of stars), long-term variations (36±6 %), periodic variations on intermediate time-scales (1±1 %) and short-term periodic variations (6±3 %). 24±6 % of the outbursting stars exhibit (semi)periodic outbursts. We close the apparent void of rare outbursters reported by Labadie-Bartz et al. (2017), and show that Be stars with infrequent outbursts are not rare. While we do not find a significant difference in the percentage of stars showing outbursts among early-type, mid-type and late-type Be stars, we show that early-type Be stars exhibit much more frequent outbursts. We have measured rising and falling times for well-covered and well-defined outbursts. Nearly all outburst events are characterized by falling times that exceed the rising times. No differences were found between early-, mid- and late-type stars; a single non-linear function adequately describes the ratio of falling time to rising time across all spectral subtypes, with the ratio being larger for short events.

The Schaake shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields

USGS Publications Warehouse

Clark, M.R.; Gangopadhyay, S.; Hay, L.; Rajagopalan, B.; Wilby, R.

2004-01-01

A number of statistical methods that are used to provide local-scale ensemble forecasts of precipitation and temperature do not contain realistic spatial covariability between neighboring stations or realistic temporal persistence for subsequent forecast lead times. To demonstrate this point, output from a global-scale numerical weather prediction model is used in a stepwise multiple linear regression approach to downscale precipitation and temperature to individual stations located in and around four study basins in the United States. Output from the forecast model is downscaled for lead times up to 14 days. Residuals in the regression equation are modeled stochastically to provide 100 ensemble forecasts. The precipitation and temperature ensembles from this approach have a poor representation of the spatial variability and temporal persistence. The spatial correlations for downscaled output are considerably lower than observed spatial correlations at short forecast lead times (e.g., less than 5 days) when there is high accuracy in the forecasts. At longer forecast lead times, the downscaled spatial correlations are close to zero. Similarly, the observed temporal persistence is only partly present at short forecast lead times. A method is presented for reordering the ensemble output in order to recover the space-time variability in precipitation and temperature fields. In this approach, the ensemble members for a given forecast day are ranked and matched with the rank of precipitation and temperature data from days randomly selected from similar dates in the historical record. The ensembles are then reordered to correspond to the original order of the selection of historical data. Using this approach, the observed intersite correlations, intervariable correlations, and the observed temporal persistence are almost entirely recovered. This reordering methodology also has applications for recovering the space-time variability in modeled streamflow. ?? 2004 American Meteorological Society.

The magnetically controlled stellar wind of HD 21699

NASA Technical Reports Server (NTRS)

Brown, D. N.; Shore, S. N.; Sonneborn, G.

1985-01-01

The discovery of a magnetically controlled stellar mass outflow in the helium-weak sn star HD 21699 = HR 1063 is reported. IUE observations show that the C IV resonance doublet is variable on the rotational time scale of about 2.5 days, and that there are no other observable spectrum variations in the UV. The magnetic field reverses sign on the rotational time scale. An interpretation of the observations in terms of magnetically structured jets is presented.

Parental Perceptions of Life Context Variables for Involvement in Their Young Children's Education

ERIC Educational Resources Information Center

Tekin, Ali Kemal

2016-01-01

The purpose of this study was to discover Turkish parents' perceptions of life context variables, including personal knowledge and skills and personal time and energy for involvement activities in their young children's education. The scales used in this study were based on parents' self-report, and included: (1) Parental Perceptions of Personal…

Advancing solar energy forecasting through the underlying physics

NASA Astrophysics Data System (ADS)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Shaping the role of 'fast' and 'slow' drivers of change in forest-shrubland socio-ecological systems.

PubMed

Ferrara, Agostino; Kelly, Claire; Wilson, Geoff A; Nolè, Angelo; Mancino, Giuseppe; Bajocco, Sofia; Salvati, Luca

2016-03-15

The temporal speeds and spatial scales at which ecosystem processes operate are often at odds with the scale and speed at which natural resources such as soil, water and vegetation are managed those. Scale mismatches often occur as a result of the time-lag between policy development, implementation and observable changes in natural capital in particular. In this study, we analyse some of the transformations that can occur in complex forest-shrubland socio-ecological systems undergoing biophysical and socioeconomic change. We use a Multiway Factor Analysis (MFA) applied to a representative set of variables to assess changes in components of natural, economic and social capitals over time. Our results indicate similarities among variables and spatial units (i.e. municipalities) which allows us to rank the variables used to describe the SES according to their rapidity of change. The novelty of the proposed framework lies in the fact that the assessment of rapidity-to-change, based on the MFA, takes into account the multivariate relationships among the system's variables, identifying the net rate of change for the whole system, and the relative impact that individual variables exert on the system itself. The aim of this study was to assess the influence of fast and slow variables on the evolution of socio-economic systems based on simplified multivariate procedures applicable to vastly different socio-economic contexts and conditions. This study also contributes to quantitative analysis methods for long-established socio-ecological systems, which may help in designing more effective, and sustainable land management strategies in environmentally sensitive areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Correlated Temporal and Spectral Variability

NASA Technical Reports Server (NTRS)

Swank, Jean H.

2007-01-01

The variability of neutron star and black hole X-ray sources has several dimensions, because of the roles played by different important time-scales. The variations on time scales of hours, weeks, and months, ranging from 50% to orders of magnitude, arise out of changes in the flow in the disk. The most important driving forces for those changes are probably various possible instabilities in the disk, though there may be effects with other dominant causes. The changes in the rate of flow appear to be associated with changes in the flow's configuration, as the accreting material approaches the compact object, for there are generally correlated changes in both the Xray spectra and the character of the faster temporal variability. There has been a lot of progress in tracking these correlations, both for Z and Atoll neutron star low-mass X-ray binaries, and for black hole binaries. I will discuss these correlations and review briefly what they tell us about the physical states of the systems.

Statistical Metadata Analysis of the Variability of Latency, Device Transfer Time, and Coordinate Position from Smartphone-Recorded Infrasound Data

NASA Astrophysics Data System (ADS)

Garces, E. L.; Garces, M. A.; Christe, A.

2017-12-01

The RedVox infrasound recorder app uses microphones and barometers in smartphones to record infrasound, low-frequency sound below the threshold of human hearing. We study a device's metadata, which includes position, latency time, the differences between the device's internal times and the server times, and the machine time, searching for patterns and possible errors or discontinuities in these scaled parameters. We highlight metadata variability through scaled multivariate displays (histograms, distribution curves, scatter plots), all created and organized through software development in Python. This project is helpful in ascertaining variability and honing the accuracy of smartphones, aiding the emergence of portable devices as viable geophysical data collection instruments. It can also improve the app and cloud service by increasing efficiency and accuracy, allowing to better document and foresee drastic natural movements like tsunamis, earthquakes, volcanic eruptions, storms, rocket launches, and meteor impacts; recorded data can later be used for studies and analysis by a variety of professions. We expect our final results to produce insight on how to counteract problematic issues in data mining and improve accuracy in smartphone data-collection. By eliminating lurking variables and minimizing the effect of confounding variables, we hope to discover efficient processes to reduce superfluous precision, unnecessary errors, and data artifacts. These methods should conceivably be transferable to other areas of software development, data analytics, and statistics-based experiments, contributing a precedent of smartphone metadata studies from geophysical rather than societal data. The results should facilitate the rise of civilian-accessible, hand-held, data-gathering mobile sensor networks and yield more straightforward data mining techniques.

Drivers and variability of the Chl fluorescence emission spectrum from the leaf through the canopy

NASA Astrophysics Data System (ADS)

Magney, T. S.; Frankenberg, C.; Grossman, K.; Koehler, P.; North, G.; Porcar-Castell, A.; Stutz, J.; Fisher, J.

2017-12-01

Recent advances in the retrieval of solar induced chlorophyll fluorescence (SIF) from remote sensing platforms provide a significant step towards mapping instantaneous plant photosynthesis across space and time. However, our current understanding of the variability and controls on the shape of the chlorophyll fluorescence (ChlF) spectrum is limited. To address these uncertainties, we have developed instrumentation to make highly resolved spectral measurements of SIF from both leaf and canopy scales. At the leaf scale, we simultaneously collected active (PAM) and passive (675-850 nm) fluorescence with photosynthesis across a range of species and conditions; and at the canopy scale, diurnal and seasonal Fraunhofer-based SIF retrievals across the red and far-red spectrum are made at four different flux tower sites (Costa Rica, Iowa (2), and Colorado). From both of these scales we are able to determine (1) the variability in steady-state spectra across species and individuals; and (2) the environmental, functional, and structural controls on SIF. Here we report on the sensitivity of SIF spectra from a singular value decomposition analysis; and present on the mechanisms - pigment concentration, species, non-photochemical and photochemical quenching, and environmental conditions - controlling SIF variability. Further, we will discuss how an improved understanding of leaf-level variability can inform canopy level SIF, and ultimately how such information may enable proper interpretation of satellite retrievals.

Energy density and variability in abundance of pigeon guillemot prey: Support for the quality-variability trade-off hypothesis

USGS Publications Warehouse

Litzow, Michael A.; Piatt, John F.; Abookire, Alisa A.; Robards, Martin D.

2004-01-01

1. The quality-variability trade-off hypothesis predicts that (i) energy density (kJ g-1) and spatial-temporal variability in abundance are positively correlated in nearshore marine fishes; and (ii) prey selection by a nearshore piscivore, the pigeon guillemot (Cepphus columba Pallas), is negatively affected by variability in abundance. 2. We tested these predictions with data from a 4-year study that measured fish abundance with beach seines and pigeon guillemot prey utilization with visual identification of chick meals. 3. The first prediction was supported. Pearson's correlation showed that fishes with higher energy density were more variable on seasonal (r = 0.71) and annual (r = 0.66) time scales. Higher energy density fishes were also more abundant overall (r = 0.85) and more patchy at a scale of 10s of km (r = 0.77). 4. Prey utilization by pigeon guillemots was strongly non-random. Relative preference, defined as the difference between log-ratio transformed proportions of individual prey taxa in chick diets and beach seine catches, was significantly different from zero for seven of the eight main prey categories. 5. The second prediction was also supported. We used principal component analysis (PCA) to summarize variability in correlated prey characteristics (energy density, availability and variability in abundance). Two PCA scores explained 32% of observed variability in pigeon guillemot prey utilization. Seasonal variability in abundance was negatively weighted by these PCA scores, providing evidence of risk-averse selection. Prey availability, energy density and km-scale variability in abundance were positively weighted. 6. Trophic interactions are known to create variability in resource distribution in other systems. We propose that links between resource quality and the strength of trophic interactions may produce resource quality-variability trade-offs.

Empirical and Theoretical Aspects of Generation and Transfer of Information in a Neuromagnetic Source Network

PubMed Central

Vakorin, Vasily A.; Mišić, Bratislav; Krakovska, Olga; McIntosh, Anthony Randal

2011-01-01

Variability in source dynamics across the sources in an activated network may be indicative of how the information is processed within a network. Information-theoretic tools allow one not only to characterize local brain dynamics but also to describe interactions between distributed brain activity. This study follows such a framework and explores the relations between signal variability and asymmetry in mutual interdependencies in a data-driven pipeline of non-linear analysis of neuromagnetic sources reconstructed from human magnetoencephalographic (MEG) data collected as a reaction to a face recognition task. Asymmetry in non-linear interdependencies in the network was analyzed using transfer entropy, which quantifies predictive information transfer between the sources. Variability of the source activity was estimated using multi-scale entropy, quantifying the rate of which information is generated. The empirical results are supported by an analysis of synthetic data based on the dynamics of coupled systems with time delay in coupling. We found that the amount of information transferred from one source to another was correlated with the difference in variability between the dynamics of these two sources, with the directionality of net information transfer depending on the time scale at which the sample entropy was computed. The results based on synthetic data suggest that both time delay and strength of coupling can contribute to the relations between variability of brain signals and information transfer between them. Our findings support the previous attempts to characterize functional organization of the activated brain, based on a combination of non-linear dynamics and temporal features of brain connectivity, such as time delay. PMID:22131968

Time-frequency dynamics of resting-state brain connectivity measured with fMRI.

PubMed

Chang, Catie; Glover, Gary H

2010-03-01

Most studies of resting-state functional connectivity using fMRI employ methods that assume temporal stationarity, such as correlation and data-driven decompositions computed across the duration of the scan. However, evidence from both task-based fMRI studies and animal electrophysiology suggests that functional connectivity may exhibit dynamic changes within time scales of seconds to minutes. In the present study, we investigated the dynamic behavior of resting-state connectivity across the course of a single scan, performing a time-frequency coherence analysis based on the wavelet transform. We focused on the connectivity of the posterior cingulate cortex (PCC), a primary node of the default-mode network, examining its relationship with both the "anticorrelated" ("task-positive") network as well as other nodes of the default-mode network. It was observed that coherence and phase between the PCC and the anticorrelated network was variable in time and frequency, and statistical testing based on Monte Carlo simulations revealed the presence of significant scale-dependent temporal variability. In addition, a sliding-window correlation procedure identified other regions across the brain that exhibited variable connectivity with the PCC across the scan, which included areas previously implicated in attention and salience processing. Although it is unclear whether the observed coherence and phase variability can be attributed to residual noise or modulation of cognitive state, the present results illustrate that resting-state functional connectivity is not static, and it may therefore prove valuable to consider measures of variability, in addition to average quantities, when characterizing resting-state networks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Wintertime East Asian Jet Stream and its Association with the Asian-Pacific-American Climate

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

The wintertime upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation over Asia. The variabilities of the jet on these time scales have been relatively well documented (e.g., Yeh et al. 1959, Palmen and Newton 1969; Zeng 1979). It has also been understood that the inter-annual variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation (Bjerknes 1966; Chang and Lau 1980; Huang and Gambo 1982; Kang and Held 1986; Tao and Chen 1987; Lau et al. 1988; Yang and Webster 1990; Ding 1992; Webster and Yang 1992; Dong et al. 1999). However, many questions remain for the year-to-year variabilities of the jet and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the jet and ENSO play different roles in modulating the APA climate? How is the jet linked to North Pacific sea surface temperature (SST) and the Pacific/North American (PNA) teleconnection pattern? In this study, we address several issues related to the wintertime EAJ with a focus on interannual time scales. We will examine the association between the jet core and ENSO, which has always been overshadowed by the relationship between ENSO and the upper-tropospheric winds over northern extratropics of the central Pacific. We will investigate the linkage of the jet to variabilities of the Asian winter monsoon, tropical convection, and upper tropospheric wave patterns. We will also explore the relationship between the jet core and extratropical S ST with an aim at providing helpful information for improving our understanding of the connection of the EAJ to surface boundary conditions. The analysis is expected to provide information that is helpful for improving regional climate predictions.

Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

2017-12-01

The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

Assessing multiscale complexity of short heart rate variability series through a model-based linear approach

NASA Astrophysics Data System (ADS)

Porta, Alberto; Bari, Vlasta; Ranuzzi, Giovanni; De Maria, Beatrice; Baselli, Giuseppe

2017-09-01

We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median = 28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median = 31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.

A statistical model for Windstorm Variability over the British Isles based on Large-scale Atmospheric and Oceanic Mechanisms

NASA Astrophysics Data System (ADS)

Kirchner-Bossi, Nicolas; Befort, Daniel J.; Wild, Simon B.; Ulbrich, Uwe; Leckebusch, Gregor C.

2016-04-01

Time-clustered winter storms are responsible for a majority of the wind-induced losses in Europe. Over last years, different atmospheric and oceanic large-scale mechanisms as the North Atlantic Oscillation (NAO) or the Meridional Overturning Circulation (MOC) have been proven to drive some significant portion of the windstorm variability over Europe. In this work we systematically investigate the influence of different large-scale natural variability modes: more than 20 indices related to those mechanisms with proven or potential influence on the windstorm frequency variability over Europe - mostly SST- or pressure-based - are derived by means of ECMWF ERA-20C reanalysis during the last century (1902-2009), and compared to the windstorm variability for the European winter (DJF). Windstorms are defined and tracked as in Leckebusch et al. (2008). The derived indices are then employed to develop a statistical procedure including a stepwise Multiple Linear Regression (MLR) and an Artificial Neural Network (ANN), aiming to hindcast the inter-annual (DJF) regional windstorm frequency variability in a case study for the British Isles. This case study reveals 13 indices with a statistically significant coupling with seasonal windstorm counts. The Scandinavian Pattern (SCA) showed the strongest correlation (0.61), followed by the NAO (0.48) and the Polar/Eurasia Pattern (0.46). The obtained indices (standard-normalised) are selected as predictors for a windstorm variability hindcast model applied for the British Isles. First, a stepwise linear regression is performed, to identify which mechanisms can explain windstorm variability best. Finally, the indices retained by the stepwise regression are used to develop a multlayer perceptron-based ANN that hindcasted seasonal windstorm frequency and clustering. Eight indices (SCA, NAO, EA, PDO, W.NAtl.SST, AMO (unsmoothed), EA/WR and Trop.N.Atl SST) are retained by the stepwise regression. Among them, SCA showed the highest linear coefficient, followed by SST in western Atlantic, AMO and NAO. The explanatory regression model (considering all time steps) provided a Coefficient of Determination (R^2) of 0.75. A predictive version of the linear model applying a leave-one-out cross-validation (LOOCV) shows an R2 of 0.56 and a relative RMSE of 4.67 counts/season. An ANN-based nonlinear hindcast model for the seasonal windstorm frequency is developed with the aim to improve the stepwise hindcast ability and thus better predict a time-clustered season over the case study. A 7 node-hidden layer perceptron is set, and the LOOCV procedure reveals a R2 of 0.71. In comparison to the stepwise MLR the RMSE is reduced a 20%. This work shows that for the British Isles case study, most of the interannual variability can be explained by certain large-scale mechanisms, considering also nonlinear effects (ANN). This allows to discern a time-clustered season from a non-clustered one - a key issue for applications e.g., in the (re)insurance industry.

Co-evolution of Climate, Soil, and Vegetation and their interplay with Hydrological Partitioning at the Catchment Scale

NASA Astrophysics Data System (ADS)

Zapata-Rios, X.; Brooks, P. D.; Troch, P. A. A.; McIntosh, J. C.

2014-12-01

Landscape, climate, and vegetation interactions play a fundamental role in controlling the distribution of available water in hillslopes and catchments. In mid-latitudes, terrain aspect can regulate surface and subsurface hydrological processes, which not only affect the partitioning of energy and precipitation on short time scales, but also soil development, vegetation characteristics on long time scales. In Redondo Peak in northern New Mexico, a volcanic resurgent dome, first order streams drain different slopes around the mountain. In this setting, we study three adjacent first order catchments that share similar physical characteristics, but drain different aspects, allowing for an empirical study of how topographically controlled microclimate and soil influence the integrated hydrological and vegetation response. From 2008 to 2012, catchments were compared for the way they partition precipitation and how vegetation responds to variable water fluxes. Meteorological variables were monitored in 5 stations around Redondo Peak and surface runoff was monitored at the catchments' outlets. Hydrological partitioning at the catchment scale was estimated with the Horton Index, defined as the ratio between vaporization and wetting and it represents a measure of catchment-scale vegetation water use. Vegetation response was estimated using remotely sensed vegetation greenness (NDVI) derived from MODIS every 16 days with a spatial resolution of 250 m. Results show that the predominantly north facing catchment has the largest and least variable baseflow and discharge, consistent with greater mineral weathering fluxes and longer water transit times. In addition, vaporization, wetting and Horton Index, as well as NDVI, are smaller in the north facing catchment compared to the south east facing catchments. The predominant terrain aspect controls soil development, which affects the partitioning of precipitation and vegetation response at the catchment scale. These results also demonstrate how landscape evolution (e.g. depth of weathering profile) can affect various hydrologic processes, including streamflow response to precipitation and water residence time. In turn these processes are first-order controls on the sensitivity of the landscape to land use and climate change.

A Rasch scaling validation of a 'core' near-death experience.

PubMed

Lange, Rense; Greyson, Bruce; Houran, James

2004-05-01

For those with true near-death experiences (NDEs), Greyson's (1983, 1990) NDE Scale satisfactorily fits the Rasch rating scale model, thus yielding a unidimensional measure with interval-level scaling properties. With increasing intensity, NDEs reflect peace, joy and harmony, followed by insight and mystical or religious experiences, while the most intense NDEs involve an awareness of things occurring in a different place or time. The semantics of this variable are invariant across True-NDErs' gender, current age, age at time of NDE, and latency and intensity of the NDE, thus identifying NDEs as 'core' experiences whose meaning is unaffected by external variables, regardless of variations in NDEs' intensity. Significant qualitative and quantitative differences were observed between True-NDErs and other respondent groups, mostly revolving around the differential emphasis on paranormal/mystical/religious experiences vs. standard reactions to threat. The findings further suggest that False-Positive respondents reinterpret other profound psychological states as NDEs. Accordingly, the Rasch validation of the typology proposed by Greyson (1983) also provides new insights into previous research, including the possibility of embellishment over time (as indicated by the finding of positive, as well as negative, latency effects) and the potential roles of religious affiliation and religiosity (as indicated by the qualitative differences surrounding paranormal/mystical/religious issues).

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.

Century to Millennium-Scale Late Quaternary Natural Climate Variability in the Midwestern United States

NASA Astrophysics Data System (ADS)

Jaumann, Peter Josef

1995-01-01

Estimates of past natural climatic variability on long time scales (centuries to millennia) are crucial in testing climate models. The process of model validation takes advantage of long general circulation model (GCM) integrations, instrumental and satellite observations, and paleoclimatic records. Here I use paleoclimatic proxy records from central North America spanning the last 150 ka to characterize climatic variability on sub-orbital time scales. A terrestrial last interglacial (~ 130 to 75 kyr BP) pollen sequence from south-central Illinois, U.S.A., contains climatic variance in frequency bands between 1 cycle/10 kyr and 1 cycle/1 kyr. The temporal variance is best developed as alternating cycles of pollen assemblages indicative of wet and dry conditions. Spectral cross-correlations between selected pollen types and potential forcings (ETP (eccentricity, tilt, precession), SPECMAP delta^{18}O) implicate oceanic and solar processes as possible mechanisms driving last interglacial vegetation and climate change in the Midwestern U.S. During the last glacial stage (LGS; 20 to 16 kyr BP) a lacustrine sequence from the central Mississippi River valley experienced major flooding events caused by intermittent melting of the Laurentide ice sheet. Rock -magnetic and grain size data confirm the physical record of flood clays. Correlation of the flood clays to the Greenland (GRIP) ice core is weak. However, the Laurentide melting events seem to fall temporally between the releases of minor LGS iceberg discharges into the North Atlantic. The GRIP delta^{18}O and the Midwestern U.S. magnetic susceptibility time series indicate sub-Milankovitch climate variability modes. Mapping, multivariate, and time series analyses of Holocene (8 to 1 ka) pollen sequences from central North America suggest spatial patterns of vegetation and climate change on sub-orbital to millennial time scales. The rate, magnitude, and spatial patterns of change varied considerably over the study region. Major climatic variance contained in several well-dated pollen time series ranges between 1 cycle/6 kyr and 1 cycle/0.6 kyr. Singular and cross -spectral analyses, again, suggest solar and oceanic forcing. Although it is difficult to attribute past climatic changes to specific forcings, the geologic record of past global change will prove invaluable in the assessment of long-term future climate change and prediction.

Reconstruction of Past Mediterranean Climate

NASA Astrophysics Data System (ADS)

García-Herrera, Ricardo; Luterbacher, Jürg; Lionello, Piero; Gonzáles-Rouco, Fidel; Ribera, Pedro; Rodó, Xavier; Kull, Christoph; Zerefos, Christos

2007-02-01

First MEDCLIVAR Workshop on Reconstruction of Past Mediterranean Climate; Pablo de Olavide University, Carmona, Spain, 8-11 November 2006; Mediterranean Climate Variability and Predictability (MEDCLIVAR; http://www.medclivar.eu) is a program that coordinates and promotes research on different aspects of Mediterranean climate. The main MEDCLIVAR goals include the reconstruction of past climate, describing patterns and mechanisms characterizing climate space-time variability, extremes at different time and space scales, coupled climate model/empirical reconstruction comparisons, seasonal forecasting, and the identification of the forcings responsible for the observed changes. The program has been endorsed by CLIVAR (Climate Variability and Predictability project) and is funded by the European Science Foundation.

Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.

Numerical Simulation of The Mediterranean Sea Using Diecast: Interaction Between Basin, Sub-basin and Local Scale Features and Natural Variability.

NASA Astrophysics Data System (ADS)

Fernández, V.; Dietrich, D. E.; Haney, R. L.; Tintoré, J.

In situ and satellite data obtained during the last ten years have shown that the circula- tion in the Mediterranean Sea is extremely complex in space, with significant features ranging from mesoscale to sub-basin and basin scale, and highly variable in time, with mesoscale to seasonal and interannual signals. Also, the steep bottom topography and the variable atmospheric conditions from one sub-basin to another, make the circula- tion to be composed of numerous energetic and narrow coastal currents, density fronts and mesoscale structures that interact at sub-basin scale with the large scale circula- tion. To simulate numerically and better understand these features, besides high grid resolution, a low numerical dispersion and low physical dissipation ocean model is required. We present the results from a 1/8z horizontal resolution numerical simula- tion of the Mediterranean Sea using DieCAST ocean model, which meets the above requirements since it is stable with low general dissipation and uses accurate fourth- order-accurate approximations with low numerical dispersion. The simulations are carried out with climatological surface forcing using monthly mean winds and relax- ation towards climatological values of temperature and salinity. The model reproduces the main features of the large basin scale circulation, as well as the seasonal variabil- ity of sub-basin scale currents that are well documented by observations in straits and channels. In addition, DieCAST brings out natural fronts and eddies that usually do not appear in numerical simulations of the Mediterranean and that lead to a natural interannual variability. The role of this intrinsic variability in the general circulation will be discussed.

Constraints on the optical polarization source in the luminous non-blazar quasar 3C 323.1 (PG 1545+210) from the photometric and polarimetric variability

NASA Astrophysics Data System (ADS)

Kokubo, Mitsuru

2017-05-01

We examine the optical photometric and polarimetric variability of the luminous type 1 non-blazar quasar 3C 323.1 (PG 1545+210). Two optical spectropolarimetric measurements taken during the periods 1996-1998 and 2003 combined with a V-band imaging-polarimetric measurement taken in 2002 reveal that (1) as noted in the literature, the polarization of 3C 323.1 is confined only to the continuum emission, I.e. the emission from the broad-line region is unpolarized; (2) the polarized flux spectra show evidence of a time-variable broad absorption feature in the wavelength range of the Balmer continuum and other recombination lines; (3) weak variability in the polarization position angle (PA) of ˜4°over a time-scale of 4-6 yr is observed and (4) the V-band total flux and the polarized flux show highly correlated variability over a time-scale of 1 yr. Taking the above-mentioned photometric and polarimetric variability properties and the results from previous studies into consideration, we propose a geometrical model for the polarization source in 3C 323.1, in which an equatorial absorbing region and an axi-asymmetric equatorial electron-scattering region are assumed to be located between the accretion disc and the broad-line region. The scattering/absorbing regions can perhaps be attributed to the accretion disc wind or flared disc surface, but further polarimetric monitoring observations for 3C 323.1 and other quasars with continuum-confined polarization are needed to probe the true physical origins of these regions.

The Flux Variability of Markarian 501 in Very High Energy Gamma Rays

NASA Astrophysics Data System (ADS)

Quinn, J.; Bond, I. H.; Boyle, P. J.; Bradbury, S. M.; Breslin, A. C.; Buckley, J. H.; Burdett, A. M.; Gordo, J. Bussons; Carter-Lewis, D. A.; Catanese, M.; Cawley, M. F.; Fegan, D. J.; Finley, J. P.; Gaidos, J. A.; Hall, T.; Hillas, A. M.; Krennrich, F.; Lamb, R. C.; Lessard, R. W.; Masterson, C.; McEnery, J. E.; Moriarty, P.; Rodgers, A. J.; Rose, H. J.; Samuelson, F. W.; Sembroski, G. H.; Srinivasan, R.; Vassiliev, V. V.; Weekes, T. C.

1999-06-01

The BL Lacertae object Markarian 501 was identified as a source of γ-ray emission at the Whipple Observatory in 1995 March. Here we present a flux variability analysis on several timescales of the 233 hr data set accumulated over 213 nights (from March 1995 to July 1998) with the Whipple Observatory 10 m atmospheric Cerenkov imaging telescope. In 1995, with the exception of a single night, the flux from Markarian 501 was constant on daily and monthly timescales and had an average flux of only 10% that of the Crab Nebula, making it the weakest very high energy source detected to date. In 1996, the average flux was approximately twice the 1995 flux and showed significant month-to-month variability. No significant day-scale variations were detected. The average γ-ray flux above ~350 GeV in the 1997 observing season rose to 1.4 times that of the Crab Nebula--14 times the 1995 discovery level--allowing a search for variability on timescales shorter than 1 day. Significant hour-scale variability was present in the 1997 data, with the shortest, observed on MJD 50,607, having a doubling time of ~2 hr. In 1998 the average emission level decreased considerably from that of 1997 (to ~20% of the Crab Nebula flux), but two significant flaring events were observed. Thus the emission from Markarian 501 shows large amplitude and rapid flux variability at very high energies, as does Markarian 421. It also shows large mean flux level variations on year-to-year timescales, behavior that has not been seen from Markarian 421 so far.

Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches

NASA Astrophysics Data System (ADS)

Egging, Rudolf Gerardus

This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in shorter solution times relative to solving the extensive-forms. Larger problems, up to 117,481 variables, were solved in extensive-form, but not when applying BD due to numerical issues. It is discussed how BD could significantly reduce the solution time of large-scale stochastic models, but various challenges remain and more research is needed to assess the potential of Benders decomposition for solving large-scale stochastic MCP. 1 www.gecforum.org

Use of Machine Learning Techniques for Identification of Robust Teleconnections to East African Rainfall Variability

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, F. R.; Funk, C.

2014-01-01

Hidden Markov models can be used to investigate structure of subseasonal variability. East African short rain variability has connections to large-scale tropical variability. MJO - Intraseasonal variations connected with appearance of "wet" and "dry" states. ENSO/IOZM SST and circulation anomalies are apparent during years of anomalous residence time in the subseasonal "wet" state. Similar results found in previous studies, but we can interpret this with respect to variations of subseasonal wet and dry modes. Reveal underlying connections between MJO/IOZM/ENSO with respect to East African rainfall.

Semi-arid vegetation response to antecedent climate and water balance windows

USGS Publications Warehouse

Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

2016-01-01

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.

Modeling the response of a standard accretion disc to stochastic viscous fluctuations

NASA Astrophysics Data System (ADS)

Ahmad, Naveel; Misra, Ranjeev; Iqbal, Naseer; Maqbool, Bari; Hamid, Mubashir

2018-01-01

The observed variability of X-ray binaries over a wide range of time-scales can be understood in the framework of a stochastic propagation model, where viscous fluctuations at different radii induce accretion rate variability that propagate inwards to the X-ray producing region. The scenario successfully explains the power spectra, the linear rms-flux relation as well as the time-lag between different energy photons. The predictions of this model have been obtained using approximate analytical solutions or empirically motivated models which take into account the effect of these propagating variability on the radiative process of complex accretion flows. Here, we study the variation of the accretion rate due to such viscous fluctuations using a hydro-dynamical code for the standard geometrically thin, gas pressure dominated α-disc with a zero torque boundary condition. Our results confirm earlier findings that the time-lag between a perturbation and the resultant inner accretion rate variation depends on the frequency (or time-period) of the perturbation. Here we have quantified that the time-lag tlag ∝f-0.54 , for time-periods less than the viscous time-scale of the perturbation radius and is nearly constant otherwise. This, coupled with radiative process would produce the observed frequency dependent time-lag between different energy bands. We also confirm that if there are random Gaussian fluctuations of the α-parameter at different radii, the resultant inner accretion rate has a power spectrum which is a power-law.

Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

USGS Publications Warehouse

Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

2013-01-01

We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.

Hydrological drivers of wetland vegetational biodiversity patterns within Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Todd, J.; Pumo, D.; Azaele, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of wetland structure. We attempt to link hydrological dynamics with vegetational distribution and species richness across Everglades National Park (ENP) using two publicly available datasets. The first, the Everglades Depth Estimation Network (EDEN),is a water-surface model which determines the median daily measure of water level across a 400mX400m grid over seven years of measurement. The second is a vegetation map and classification system at the 1:15,000 scale which categorizes vegetation within the Everglades into 79 community types. From these data, we have studied the probabilistic structure of the frequency, duration, and depth of hydroperiods. Preliminary results indicate that the percentage of time a location is inundated is a principal structuring variable with individual communities responding differently. For example, sawgrass appears to be more of a generalist community as it is found across a wide range of time inundated percentages while spike rush has a more restricted distribution and favors wetter environments disproportionately more than predicted at random. Further, the diversity of vegetation communities (e.g. a measure of biodiversity) found across a hydrologic variable does not necessarily match the distribution function for that variable on the landscape. For instance, the number of communities does not differ across the percentage of time inundated. Different measures of vegetation biodiversity such as the local number of community types are also studied at different spatial scales with some characteristics, like the slope of the semi-logarithmic relation between rank and occupancy, found to be robust to scale changes. The ENP offers an expansive natural environment in which to study how vegetational dynamics and community composition are affected by hydrologic variables from the small scale (at the individual community level) to the large (biodiversity measures at differing spatial scales).

A High-Resolution Record of Holocene Climate Variability from a Western Canadian Coastal Inlet

NASA Astrophysics Data System (ADS)

Dallimore, A.; Thomson, R. E.; Enkin, R. J.; Kulikov, E. A.; Bertram, M. A.; Wright, C. A.; Southon, J. R.; Barrie, J. V.; Baker, J.; Pienitz, R.; Calvert, S. E.; Chang, A. S.; Pedersen, T. F.

2004-12-01

Conditions within the Pacific Ocean have a major effect on the climate of northwestern North America. High resolution records of present and past northeast Pacific climate are revealed in our multi-disciplinary study of annually laminated marine sediments from anoxic coastal inlets of British Columbia. Past climate conditions for the entire Holocene are recorded in the sediment record contained in a 40 meter, annually laminated marine sediment core taken in Effingham Inlet, on the west coast of Vancouver Island, British Columbia, from the French ship the Marion Dufresne, as part of the international IMAGES program. By combining our eight year continuous instrument record of modern coastal ocean dynamics and climate with high-resolution analysis of depositional processes, we have been able to develop proxy measurements of past climatic and oceanographic changes on annual to millennial time scales. Results indicate that regional climate has oscillated on a variety of time scales throughout the Holocene. At times, climatic change has been dramatically rapid. We are also developing digital methods for statistical time-series analyses of physical sediment properties through the Holocene in order to obtain a more objective quantitative approach for detecting cyclicity in our data. Results of the time series analysis of lamination thickness reveals statistically significant spectral peaks of climate scale variability at established decadal to century time scales. These in turn may be related to solar cycles and quasi-cyclical ocean processes such as the Pacific Decadal Oscillation. However, the annually laminated time series are periodically interrupted by massive mud intervals which are related to bottom currents and at times paleo-seismic events, illustrating the need for a full understanding of modern oceanographic and sedimentation processes, so an accurate proxy record of past climate can be established.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

NASA Astrophysics Data System (ADS)

Lerma, Claudia; Echeverría, Juan C.; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α1) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α1sign) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α1 and α1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α1magn) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α1magn > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α1 and α1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

PubMed

Lerma, Claudia; Echeverría, Juan C; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α 1 ) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α 1sign ) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α 1 and α 1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α 1magn ) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α 1magn  > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α 1 and α 1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Temporal clustering of floods in Germany: Do flood-rich and flood-poor periods exist?

NASA Astrophysics Data System (ADS)

Merz, Bruno; Nguyen, Viet Dung; Vorogushyn, Sergiy

2016-10-01

The repeated occurrence of exceptional floods within a few years, such as the Rhine floods in 1993 and 1995 and the Elbe and Danube floods in 2002 and 2013, suggests that floods in Central Europe may be organized in flood-rich and flood-poor periods. This hypothesis is studied by testing the significance of temporal clustering in flood occurrence (peak-over-threshold) time series for 68 catchments across Germany for the period 1932-2005. To assess the robustness of the results, different methods are used: Firstly, the index of dispersion, which quantifies the departure from a homogeneous Poisson process, is investigated. Further, the time-variation of the flood occurrence rate is derived by non-parametric kernel implementation and the significance of clustering is evaluated via parametric and non-parametric tests. Although the methods give consistent overall results, the specific results differ considerably. Hence, we recommend applying different methods when investigating flood clustering. For flood estimation and risk management, it is of relevance to understand whether clustering changes with flood severity and time scale. To this end, clustering is assessed for different thresholds and time scales. It is found that the majority of catchments show temporal clustering at the 5% significance level for low thresholds and time scales of one to a few years. However, clustering decreases substantially with increasing threshold and time scale. We hypothesize that flood clustering in Germany is mainly caused by catchment memory effects along with intra- to inter-annual climate variability, and that decadal climate variability plays a minor role.

Spatiotemporal predictability of schooling and nonschooling prey of Pigeon Guillemots

USGS Publications Warehouse

Litzow, Michael A.; Piatt, John F.; Abookire, Alisa A.; Speckman, Suzann G.; Arimitsu, Mayumi L.; Figurski, Jared D.

2004-01-01

Low spatiotemporal variability in the abundance of nonschooling prey might allow Pigeon Guillemots (Cepphus columba) to maintain the high chick provisioning rates that are characteristic of the species. We tested predictions of this hypothesis with data collected with beach seines and scuba and hydroacoustic surveys in Kachemak Bay, Alaska, during 1996–1999. Coefficients of variability were 20–211% greater for schooling than nonschooling prey on day, seasonal, and km scales. However, the proportion of schooling prey in chick diets explained relatively little variability in Pigeon Guillemot meal delivery rates at the scale of hours (r2 = 0.07) and weeks (r2 = 0.19). Behavioral adaptations such as flexible time budgets likely ameliorate the negative effects of high resource variability, but we propose that these adaptations are only effective when schooling prey are available at distances well below the maximum foraging range of the species.

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

NASA Technical Reports Server (NTRS)

Pikkujamsa, S. M.; Makikallio, T. H.; Sourander, L. B.; Raiha, I. J.; Puukka, P.; Skytta, J.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

Extruder scale-up assessment in the process of extrusion-spheronization: comparison of radial and axial systems by a design of experiments approach.

PubMed

Désiré, Amélie; Paillard, Bruno; Bougaret, Joël; Baron, Michel; Couarraze, Guy

2013-02-01

Scaling-up the extrusion-spheronization process involves the separate scale-up of each of the five process steps: dry mixing, granulation, extrusion, spheronization, and drying. The aim of the study was to compare two screw extrusion systems regarding their suitability for scaling-up. Two drug substances of high- and low-solubility in water were retained at different concentrations as formulation variables. Different spheronization times were tested. The productivity of the process was followed up using the extrusion rate and yield. Pellets were characterized by their size and shape, and by their structural and mechanical properties. A response surface design of experiments was built to evaluate the influence of the different variables and their interactions on each response, and to select the type of extrusion which provides the best results in terms of product quality, the one which shows less influence on the product after scale-up ("scalability") and when the formula used changes ("robustness"), and the one which allows the possibility to adjust pellet properties with spheronization variables ("flexibility"). Axial system showed the best characteristics in terms of product quality at lab and industrial scales, the best robustness at industrial scale, and the best scalability, by comparison with radial system. Axial system thus appeared as the easiest scaled-up system. Compared to lab scale, the conclusions observed at industrial scale were the same in terms of product quality, but different for robustness and flexibility, which confirmed the importance to test the systems at industrial scale before acquiring the equipment.

Trend and variability in western and central Africa streamflow, and their relation to climate variability between 1950 and 2010

NASA Astrophysics Data System (ADS)

Sidibe, Moussa; Dieppois, Bastien; Mahé, Gil; Paturel, Jean-Emmanuel; Rouché, Nathalie; Amoussou, Ernest; Anifowose, Babatunde; Lawler, Damian

2017-04-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s. This triggered many studies investigating rainfall variability and its impacts on food production systems. However, most studies were focused at the catchment scale. In this study, we examine how rainfall variability has impacted on river flow at the subcontinental scale between 1950 and 2010, as well as the key large-scale controls on this relationship. For the first time, we establish a complete, gap-filled, monthly streamflow data set, which extends from 1950 to 2010, over the western and central African region. To achieve this, we used linear regression modelling across and between 600 flow gauging stations (see initial database information at http://www.hydrosciences.fr/sierem/index_en.htm). Streamflow trend and variability are then seasonally assessed at this subcontinental scale and compared to those observed in three different rainfall data sets (i.e. CRU TS3.24, GPCC V7, IRD-HSM). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In particular, we note that the recent post 1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). Using multi-temporal trend and continuous wavelet analysis, the time-evolution of western and central African river flows are analysed, and are all characterized by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns, such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and/or the Pacific Decadal Oscillation. Furthermore, hitherto-poorly understood hydroclimatic processes related to these teleconnections at decadal timescales will be examined in this study. Influences of the catchment properties (e.g. size, shape, vegetation and landuse cover, soil type, ground-water level, direction of stream flow across climate zones) on these decadal fluctuations in river flows will also be assessed. This study therefore aims to improve the ability of current regional and global climate models to simulate such ranges of variability, to significantly improve regional hydroclimate understanding, as a means for improving the development of future scenarios for water resources in western and central Africa.

Identification of varying time scales in sediment transport using the Hilbert-Huang Transform method

NASA Astrophysics Data System (ADS)

Kuai, Ken Z.; Tsai, Christina W.

2012-02-01

SummarySediment transport processes vary at a variety of time scales - from seconds, hours, days to months and years. Multiple time scales exist in the system of flow, sediment transport and bed elevation change processes. As such, identification and selection of appropriate time scales for flow and sediment processes can assist in formulating a system of flow and sediment governing equations representative of the dynamic interaction of flow and particles at the desired details. Recognizing the importance of different varying time scales in the fluvial processes of sediment transport, we introduce the Hilbert-Huang Transform method (HHT) to the field of sediment transport for the time scale analysis. The HHT uses the Empirical Mode Decomposition (EMD) method to decompose a time series into a collection of the Intrinsic Mode Functions (IMFs), and uses the Hilbert Spectral Analysis (HSA) to obtain instantaneous frequency data. The EMD extracts the variability of data with different time scales, and improves the analysis of data series. The HSA can display the succession of time varying time scales, which cannot be captured by the often-used Fast Fourier Transform (FFT) method. This study is one of the earlier attempts to introduce the state-of-the-art technique for the multiple time sales analysis of sediment transport processes. Three practical applications of the HHT method for data analysis of both suspended sediment and bedload transport time series are presented. The analysis results show the strong impact of flood waves on the variations of flow and sediment time scales at a large sampling time scale, as well as the impact of flow turbulence on those time scales at a smaller sampling time scale. Our analysis reveals that the existence of multiple time scales in sediment transport processes may be attributed to the fractal nature in sediment transport. It can be demonstrated by the HHT analysis that the bedload motion time scale is better represented by the ratio of the water depth to the settling velocity, h/ w. In the final part, HHT results are compared with an available time scale formula in literature.

Fine Scale Baleen Whale Behavior Observed via Tagging Over Daily Time Scales

DTIC Science & Technology

2013-09-30

sei whales) and the diel vertical migration behavior of their copepod prey. I hypothesize that (1) right whales track the diel vertical migration of... copepods by feeding near the bottom during the day and at the surface at night, and (2) sei whales are unable to feed on copepods at depth during the...day, and are therefore restricted to feeding on copepods at the surface only. Because copepod diel vertical migration is variable over time (days to

National Earthquake Information Center Seismic Event Detections on Multiple Scales

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W. L.; Benz, H.; Earle, P. S.; Soto-Cordero, L.; Johnson, C. E.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (NEIC) monitors seismicity on local, regional, and global scales using automatic picks from more than 2,000 near-real time seismic stations. This presents unique challenges in automated event detection due to the high variability in data quality, network geometries and density, and distance-dependent variability in observed seismic signals. To lower the overall detection threshold while minimizing false detection rates, NEIC has begun to test the incorporation of new detection and picking algorithms, including multiband (Lomax et al., 2012) and kurtosis (Baillard et al., 2014) pickers, and a new bayesian associator (Glass 3.0). The Glass 3.0 associator allows for simultaneous processing of variably scaled detection grids, each with a unique set of nucleation criteria (e.g., nucleation threshold, minimum associated picks, nucleation phases) to meet specific monitoring goals. We test the efficacy of these new tools on event detection in networks of various scales and geometries, compare our results with previous catalogs, and discuss lessons learned. For example, we find that on local and regional scales, rapid nucleation of small events may require event nucleation with both P and higher-amplitude secondary phases (e.g., S or Lg). We provide examples of the implementation of a scale-independent associator for an induced seismicity sequence (local-scale), a large aftershock sequence (regional-scale), and for monitoring global seismicity. Baillard, C., Crawford, W. C., Ballu, V., Hibert, C., & Mangeney, A. (2014). An automatic kurtosis-based P-and S-phase picker designed for local seismic networks. Bulletin of the Seismological Society of America, 104(1), 394-409. Lomax, A., Satriano, C., & Vassallo, M. (2012). Automatic picker developments and optimization: FilterPicker - a robust, broadband picker for real-time seismic monitoring and earthquake early-warning, Seism. Res. Lett. , 83, 531-540, doi: 10.1785/gssrl.83.3.531.

Modelling of Sub-daily Hydrological Processes Using Daily Time-Step Models: A Distribution Function Approach to Temporal Scaling

NASA Astrophysics Data System (ADS)

Kandel, D. D.; Western, A. W.; Grayson, R. B.

2004-12-01

Mismatches in scale between the fundamental processes, the model and supporting data are a major limitation in hydrologic modelling. Surface runoff generation via infiltration excess and the process of soil erosion are fundamentally short time-scale phenomena and their average behaviour is mostly determined by the short time-scale peak intensities of rainfall. Ideally, these processes should be simulated using time-steps of the order of minutes to appropriately resolve the effect of rainfall intensity variations. However, sub-daily data support is often inadequate and the processes are usually simulated by calibrating daily (or even coarser) time-step models. Generally process descriptions are not modified but rather effective parameter values are used to account for the effect of temporal lumping, assuming that the effect of the scale mismatch can be counterbalanced by tuning the parameter values at the model time-step of interest. Often this results in parameter values that are difficult to interpret physically. A similar approach is often taken spatially. This is problematic as these processes generally operate or interact non-linearly. This indicates a need for better techniques to simulate sub-daily processes using daily time-step models while still using widely available daily information. A new method applicable to many rainfall-runoff-erosion models is presented. The method is based on temporal scaling using statistical distributions of rainfall intensity to represent sub-daily intensity variations in a daily time-step model. This allows the effect of short time-scale nonlinear processes to be captured while modelling at a daily time-step, which is often attractive due to the wide availability of daily forcing data. The approach relies on characterising the rainfall intensity variation within a day using a cumulative distribution function (cdf). This cdf is then modified by various linear and nonlinear processes typically represented in hydrological and erosion models. The statistical description of sub-daily variability is thus propagated through the model, allowing the effects of variability to be captured in the simulations. This results in cdfs of various fluxes, the integration of which over a day gives respective daily totals. Using 42-plot-years of surface runoff and soil erosion data from field studies in different environments from Australia and Nepal, simulation results from this cdf approach are compared with the sub-hourly (2-minute for Nepal and 6-minute for Australia) and daily models having similar process descriptions. Significant improvements in the simulation of surface runoff and erosion are achieved, compared with a daily model that uses average daily rainfall intensities. The cdf model compares well with a sub-hourly time-step model. This suggests that the approach captures the important effects of sub-daily variability while utilizing commonly available daily information. It is also found that the model parameters are more robustly defined using the cdf approach compared with the effective values obtained at the daily scale. This suggests that the cdf approach may offer improved model transferability spatially (to other areas) and temporally (to other periods).

Brain Dynamics of Aging: Multiscale Variability of EEG Signals at Rest and during an Auditory Oddball Task1,2,3

PubMed Central

Perdikis, Dionysios; Müller, Viktor; Blanc, Jean-Luc; Huys, Raoul; Temprado, Jean-Jacques

2015-01-01

Abstract The present work focused on the study of fluctuations of cortical activity across time scales in young and older healthy adults. The main objective was to offer a comprehensive characterization of the changes of brain (cortical) signal variability during aging, and to make the link with known underlying structural, neurophysiological, and functional modifications, as well as aging theories. We analyzed electroencephalogram (EEG) data of young and elderly adults, which were collected at resting state and during an auditory oddball task. We used a wide battery of metrics that typically are separately applied in the literature, and we compared them with more specific ones that address their limits. Our procedure aimed to overcome some of the methodological limitations of earlier studies and verify whether previous findings can be reproduced and extended to different experimental conditions. In both rest and task conditions, our results mainly revealed that EEG signals presented systematic age-related changes that were time-scale-dependent with regard to the structure of fluctuations (complexity) but not with regard to their magnitude. Namely, compared with young adults, the cortical fluctuations of the elderly were more complex at shorter time scales, but less complex at longer scales, although always showing a lower variance. Additionally, the elderly showed signs of spatial, as well as between, experimental conditions dedifferentiation. By integrating these so far isolated findings across time scales, metrics, and conditions, the present study offers an overview of age-related changes in the fluctuation electrocortical activity while making the link with underlying brain dynamics. PMID:26464983

Use of soil moisture dynamics and patterns for the investigation of runoff generation processes with emphasis on preferential flow

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2007-08-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

Treesearch

Tana Wood; M. Detto; W.L. Silver

2013-01-01

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal...

Complex UV/X-ray variability of 1H 0707-495

NASA Astrophysics Data System (ADS)

Pawar, P. K.; Dewangan, G. C.; Papadakis, I. E.; Patil, M. K.; Pal, Main; Kembhavi, A. K.

2017-12-01

We study the relationship between the UV and X-ray variability of the narrow-line Seyfert 1 galaxy 1H 0707-495. Using a year-long Swift monitoring and four long XMM-Newton observations, we perform cross-correlation analyses of the UV and X-ray light curves, on both long and short time-scales. We also perform time-resolved X-ray spectroscopy on 1-2 ks scale, and study the relationship between the UV emission and the X-ray spectral components - soft X-ray excess and a power law. We find that the UV and X-ray variations anticorrelate on short, and possibly on long time-scales as well. Our results rule out reprocessing as the dominant mechanism for the UV variability, as well as the inward propagating fluctuations in the accretion rate. Absence of a positive correlation between the photon index and the UV flux suggests that the observed UV emission is unlikely to be the seed photons for the thermal Comptonization. We find a strong correlation between the continuum flux and the soft-excess temperature which implies that the soft excess is most likely the reprocessed X-ray emission in the inner accretion disc. Strong X-ray heating of the innermost regions in the disc, due to gravitational light bending, appears to be an important effect in 1H 0707-495, giving rise to a significant fraction of the soft excess as reprocessed thermal emission. We also find indications for a non-static, dynamic X-ray corona, where either the size or height (or both) vary with time.

Improved short-term variability in the thermosphere-ionosphere-mesosphere-electrodynamics general circulation model

NASA Astrophysics Data System (ADS)

Häusler, K.; Hagan, M. E.; Baumgaertner, A. J. G.; Maute, A.; Lu, G.; Doornbos, E.; Bruinsma, S.; Forbes, J. M.; Gasperini, F.

2014-08-01

We report on a new source of tidal variability in the National Center for Atmospheric Research thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM). Lower boundary forcing of the TIME-GCM for a simulation of November-December 2009 based on 3-hourly Modern-Era Retrospective Analysis for Research and Application (MERRA) reanalysis data includes day-to-day variations in both diurnal and semidiurnal tides of tropospheric origin. Comparison with TIME-GCM results from a heretofore standard simulation that includes climatological tropospheric tides from the global-scale wave model reveal evidence of the impacts of MERRA forcing throughout the model domain, including measurable tidal variability in the TIME-GCM upper thermosphere. Additional comparisons with measurements made by the Gravity field and steady-state Ocean Circulation Explorer satellite show improved TIME-GCM capability to capture day-to-day variations in thermospheric density for the November-December 2009 period with the new MERRA lower boundary forcing.

Meridional Propagation of the MJO/ISO and Prediction of Off-equatorial Monsoon Variability

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, S.; Suarez, M.; Pegion, P.; Bacmeister, J.; Waliser, D.

2004-01-01

In this study we examine the links between tropical heating, the Madden Julian Oscillation (MJO)/Intraseasonal Oscillation (ISO), and the off-equatorial monsoon development. We examine both observations and idealized "MJO heating" experiments employing the NASA Seasonal-Interannual Prediction Project (NSIPP) atmospheric general circulation model (AGCM). In the simulations, the model is forced by climatological SST and an idealized eastward propagating heating profile that is meant to mimic the canonical heating associated with the MJO in the Indian Ocean and western Pacific. The observational analysis highlights the strong link between the Indian summer monsoon and the tropical ISO/MJO activity and heating. Here we focus on the potential for skillful predictions of the monsoon on subseasonal time scales associated with the meridional propagation of the ISOMJO. In particular, we show that the variability of the Indian summer monsoon lags behind the variability of tropical ISOMJO heating by about 15 days when the tropical heating is around 60E and 90E. This feature of the ISOMJO is reproduced in the AGCM experiments with the idealized eastward propagating MJO-like heating, suggesting that models with realistic ISOM0 variability should provide useful skill of monsoon breaks and surges on subseasonal time scales.

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.

A Study of Mexican Free-Tailed Bat Chirp Syllables: Bayesian Functional Mixed Models for Nonstationary Acoustic Time Series.

PubMed

Martinez, Josue G; Bohn, Kirsten M; Carroll, Raymond J; Morris, Jeffrey S

2013-06-01

We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to capture correlation within the spectrogram in our modeling and obtain adaptive regularization of the estimates and inference for the regions-specific spectrograms. Our model includes random effect spectrograms at the bat level to account for correlation among chirps from the same bat, and to assess relative variability in chirp spectrograms within and between bats. The modeling of spectrograms using functional mixed models is a general approach for the analysis of replicated nonstationary time series, such as our acoustical signals, to relate aspects of the signals to various predictors, while accounting for between-signal structure. This can be done on raw spectrograms when all signals are of the same length, and can be done using spectrograms defined on a relative time scale for signals of variable length in settings where the idea of defining correspondence across signals based on relative position is sensible.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

NASA Astrophysics Data System (ADS)

Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

2016-04-01

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

Improved Uncertainty Quantification in Groundwater Flux Estimation Using GRACE

NASA Astrophysics Data System (ADS)

Reager, J. T., II; Rao, P.; Famiglietti, J. S.; Turmon, M.

2015-12-01

Groundwater change is difficult to monitor over large scales. One of the most successful approaches is in the remote sensing of time-variable gravity using NASA Gravity Recovery and Climate Experiment (GRACE) mission data, and successful case studies have created the opportunity to move towards a global groundwater monitoring framework for the world's largest aquifers. To achieve these estimates, several approximations are applied, including those in GRACE processing corrections, the formulation of the formal GRACE errors, destriping and signal recovery, and the numerical model estimation of snow water, surface water and soil moisture storage states used to isolate a groundwater component. A major weakness in these approaches is inconsistency: different studies have used different sources of primary and ancillary data, and may achieve different results based on alternative choices in these approximations. In this study, we present two cases of groundwater change estimation in California and the Colorado River basin, selected for their good data availability and varied climates. We achieve a robust numerical estimate of post-processing uncertainties resulting from land-surface model structural shortcomings and model resolution errors. Groundwater variations should demonstrate less variability than the overlying soil moisture state does, as groundwater has a longer memory of past events due to buffering by infiltration and drainage rate limits. We apply a model ensemble approach in a Bayesian framework constrained by the assumption of decreasing signal variability with depth in the soil column. We also discuss time variable errors vs. time constant errors, across-scale errors v. across-model errors, and error spectral content (across scales and across model). More robust uncertainty quantification for GRACE-based groundwater estimates would take all of these issues into account, allowing for more fair use in management applications and for better integration of GRACE-based measurements with observations from other sources.

Diurnal variability in carbon and nitrogen pools within Chesapeake Bay and northern Gulf of Mexico: implications for future ocean color satellite sensors

NASA Astrophysics Data System (ADS)

Mannino, A.; Novak, M. G.; Tzortziou, M.; Salisbury, J.

2016-02-01

Relative to their areal extent, estuaries and coastal ocean ecosystems contribute disproportionately more to global biogeochemical cycling of carbon, nitrogen and other elements compared to the open ocean. Applying ocean color satellite data to study biological and biogeochemical processes within coastal ecosystems is challenging due to the complex mixtures of aquatic constituents derived from terrestrial, anthropogenic, and marine sources, human-impacted atmospheric properties, presence of clouds during satellite overpass, fine-scale spatial gradients, and time-varying processes on diurnal scales that cannot be resolved with current sensors. On diurnal scales, biological, photochemical, and biogeochemical processes are regulated by the variation in solar radiation. Other physical factors, such as tides, river discharge, estuarine and coastal ocean circulation, wind-driven mixing, etc., impart further variability on biological and biogeochemical processes on diurnal to multi-day time scales. Efforts to determine the temporal frequency required from a NASA GEO-CAPE ocean color satellite sensor to discern diurnal variability C and N stocks, fluxes and productivity culminated in field campaigns in the Chesapeake Bay and northern Gulf of Mexico. Near-surface drogues were released and tracked in quasi-lagrangian space to monitor hourly changes in community production, C and N stocks, and optical properties. While only small diurnal changes were observed in dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) absorption in Chesapeake Bay, substantial variation in particulate organic carbon (POC) and nitrogen (PN), chlorophyll-a, and inorganic nitrogen (DIN) were measured. Similar or greater diurnal changes in POC, PN, chlorophyll-a and DIN were found in Gulf of Mexico nearshore and offshore sites. These results suggest that satellite observations at hourly frequency are desirable to capture diurnal variability in carbon and nitrogen stocks, fluxes and productivity within coastal ecosystems.

Global Scale Remote Sensing Monitoring of Endorheic Lake Systems

NASA Astrophysics Data System (ADS)

Scuderi, L. A.

2010-12-01

Semi-arid regions of the world contain thousands of endorheic lakes in large shallow basins. Due to their generally remote locations few are continuously monitored. Documentation of recent variability is essential to assessing how endorheic lakes respond to short-term meteorological conditions and longer-term decadal-scale climatic variability and is critical in determining future disturbance of hydrological regimes with respect to predicted warming and drying in the mid-latitudes. Short- and long-term departures from climatic averages, rapid environmental shifts and increased population pressures may result in significant fluctuations in the hydrologic budgets of these lakes and adversely impact endorheic lake/basin ecosystems. Information on flooding variability is also critical in estimating changes in P/E balances and on the production of exposed and easily deflated surfaces that may impact dust loading locally and regionally. In order to provide information on how these lakes respond we need to understand how entire systems respond hydrologically to different climatic inputs. This requires monitoring and analysis of regional to continental-scale systems. To date, this level of monitoring has not been achieved in an operational system. In order to assess the possibility of creating a global-scale lake inundation database we analyzed two contrasting lake systems in western North America (Mexico and New Mexico, USA) and China (Inner Mongolia). We asked two major questions: 1) is it possible to quickly and accurately quantify current lake inundation events in near real time using remote sensing? and, 2) is it possible to differentiate variable meteorological sources and resultant lake inundation responses using this type of database? With respect to these results we outline an automated lake monitoring approach using MODIS data and real-time processing systems that may provide future global monitoring capabilities.

An 1800-yr record of decadal-scale hydroclimatic variability in the upper Arkansas River basin from bristlecone pine

USGS Publications Warehouse

Woodhouse, C.A.; Pederson, G.T.; Gray, S.T.

2011-01-01

Bristlecone pine trees are exceptionally long-lived, and with the incorporation of remnant material have been used to construct multi-millennial length ring-width chronologies. These chronologies can provide valuable information about past temperature and moisture variability. In this study, we outline a method to build a moisture-sensitive bristlecone chronology and assess the robustness and consistency of this sensitivity over the past 1200. yr using new reconstructions of Arkansas River flow (AD 1275-2002 and 1577-2002) and the summer Palmer Drought Sensitivity Index. The chronology, a composite built from parts of three collections in the central Rocky Mountains, is a proxy for decadal-scale moisture variability for the past 18 centuries. Since the sample size is small in some portions of the time series, the chronology should be considered preliminary; the timing and duration of drought events are likely the most robust characteristics. This chronology suggests that the region experienced increased aridity during the medieval period, as did much of western North America, but that the timing and duration of drought episodes within this period were somewhat different from those in other western locations, such as the upper Colorado River basin. ?? 2010 University of Washington.

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming.

PubMed

Lin, Yong; Franzke, Christian L E

2015-08-11

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary.

Exploring the Linkage of Sea Surface Temperature Variability on Three Spatial Scales

NASA Astrophysics Data System (ADS)

Luo, L.; Capone, D. G.; Hutchins, D.; Kiefer, D.

2011-12-01

As part of a project examining climate change in the Southern California Bight at the University of Southern California, we studied the linkage of the variability of sea surface temperature across three nested spatial scales, the north Pacific Basin, the West Coast of North American, and the Southern California Bight. Specifically, we analyzed daily GHRSST images between September 1981 and July 2009. In order to remove seasonal changes in temperature and focus upon differences between years, we calculate weekly mean temperature for each pixel from the time series, and then subjected the anomalies for the 3 spatial scales to empirical orthogonal function (EOF) analysis. The corresponding temporal expansion coefficients and spatial components (eigenvector) for each EOF mode were then generated to examine the temporal and spatial patterns of SST change. The results showed that the El Nino Southern Oscillation (ENSO) has a clear influence on the SST variability across all the three spatial scales, especially the 1st EOF mode which represents the largest variance. The comparison between the time coefficients of the 1st EOF mode and the Oceanic Nino Index (ONI) suggested that the EOF mode 1 of the Pacific Basin region matched well with almost all the El Nino and La Nina signals while the West Coast of North American captured only the strong signals and the Southern California Bight captures still fewer of the signals. This clearly indicated that the Southern California Bight is relatively insensitive to ENSO signal relative to other locations along the West Coast. The 1st EOF Mode for the West Coast of North American was also clearly influenced by upwelling. The cross correlation coefficient between each pair of the EOF mode 1 temporal expansion coefficients for the three spatial scales suggested that they were significantly correlated to each other. The effect of the Pacific Decadal Oscillation (PDO) on the SST change was also demonstrated by the temporal variability of the temporal expansion coefficients of the 2nd EOF mode. However, the correlations of 2nd EOF mode time coefficients between the three scales appeared relatively low compared the 1st EOF mode. In summary sea surface temperature in the Southern California Bight behaves like a node that is relatively insensitive to ENSO, PDO, and upwelling signals.

The impact of land use change and hydroclimatic variability on landscape connectivity dynamics across surface water networks at subcontinental scale

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Bishop-Taylor, R.; Broich, M.

2017-12-01

Land use (LU) change and hydroclimatic variability affect spatiotemporal landscape connectivity dynamics, important for species movement and dispersal. Despite the fact that LU change can strongly influence dispersal potential over time, prior research has only focused on the impacts of dynamic changes in the distribution of potential habitats. We used 8 time-steps of historical LU together with a Landsat-derived time-series of surface water habitat dynamics (1986-2011) over the Murray-Darling Basin (MDB), a region with extreme hydroclimatic variability, impacted by LU changes. To assess how changing LU and hydroclimatic variability affect landscape connectivity across time, we compared 4 scenarios, namely one where both climate and LU are dynamic over time, one where climate is kept steady (i.e. a median surface water extent layer), and two scenarios where LU is kept steady (i.e. resistance values associated with the most recent or the first LU layer). We used circuit theory to assign landscape features with `resistance' costs and graph theory network analysis, with surface water habitats as `nodes' connected by dispersal paths or `edges' Findings comparing a dry and an average season show high differences in number of nodes (14581 vs 21544) and resistance distances. The combined effect of LU change and landscape wetness was lower than expected, likely a function of the large, MDB-wide, aggregation scale. Spatially explicit analyses are expected to identify areas where the synergistic effect of LU change and landscape wetness greatly reduce or increase landscape connectivity, as well as areas where the two effects cancel each other out.

Apparent multifractality of self-similar Lévy processes

NASA Astrophysics Data System (ADS)

Zamparo, Marco

2017-07-01

Scaling properties of time series are usually studied in terms of the scaling laws of empirical moments, which are the time average estimates of moments of the dynamic variable. Nonlinearities in the scaling function of empirical moments are generally regarded as a sign of multifractality in the data. We show that, except for the Brownian motion, this method fails to disclose the correct monofractal nature of self-similar Lévy processes. We prove that for this class of processes it produces apparent multifractality characterised by a piecewise-linear scaling function with two different regimes, which match at the stability index of the considered process. This result is motivated by previous numerical evidence. It is obtained by introducing an appropriate stochastic normalisation which is able to cure empirical moments, without hiding their dependence on time, when moments they aim at estimating do not exist.

Arabic versions of the sleep timing questionnaire and the composite scale of morningness.

PubMed

Mansour, Hader; Tobar, Salwa; Fathi, Warda; Ibrahim, Ibtihal; Wood, Joel; Elassy, Mai; Elsayed, Hanan; Yassin, Amal; Salah, Hala; Eissa, Ahmed; El-Boraie, Hala; El-Boraie, Osama; Dobea, Ahmed; Osama, Haitham; Gomaa, Zeinab; El-Bahaei, Wafaa; Monk, Timothy H; Nimgaonkar, Vishwajit L

2015-02-01

To develop Arabic versions of English language questionnaires to estimate morningness/eveningness and sleep variables. We translated the Composite scale of morningness (CSM) and the sleep timing questionnaire (STQ) [with added siesta questions] into Arabic; the Arabic versions were then back translated. The revised Arabic and the original English versions were next administered to bi-lingual Egyptians using a crossover design (n=25). The Arabic versions of both scales were subsequently administered to an independent Egyptian sample (n=79) and the siesta variables examined in relation to the CSM. Satisfactory correlations were present between the English and Arabic versions for total CSM scores (Spearman's ρ=0.90, p<0.001). All but one of the STQ variables were significantly correlated (Spearman's ρ=0.45-0.88, p≤0.05). In the Arabic version, the frequency of siesta naps per week was significantly correlated with the total CSM score, with evening types taking more naps (Spearman's ρ=-0.23, p≤0.05). Arabic versions of the STQ and CSM have been developed in Egypt, and are freely available. They can be used for behavioral research related to sleep and circadian function and can be adapted for use in other Arab speaking populations. Copyright © 2014 Elsevier B.V. All rights reserved.

Trend assessment: applications for hydrology and climate research

NASA Astrophysics Data System (ADS)

Kallache, M.; Rust, H. W.; Kropp, J.

2005-02-01

The assessment of trends in climatology and hydrology still is a matter of debate. Capturing typical properties of time series, like trends, is highly relevant for the discussion of potential impacts of global warming or flood occurrences. It provides indicators for the separation of anthropogenic signals and natural forcing factors by distinguishing between deterministic trends and stochastic variability. In this contribution river run-off data from gauges in Southern Germany are analysed regarding their trend behaviour by combining a deterministic trend component and a stochastic model part in a semi-parametric approach. In this way the trade-off between trend and autocorrelation structure can be considered explicitly. A test for a significant trend is introduced via three steps: First, a stochastic fractional ARIMA model, which is able to reproduce short-term as well as long-term correlations, is fitted to the empirical data. In a second step, wavelet analysis is used to separate the variability of small and large time-scales assuming that the trend component is part of the latter. Finally, a comparison of the overall variability to that restricted to small scales results in a test for a trend. The extraction of the large-scale behaviour by wavelet analysis provides a clue concerning the shape of the trend.

Mesoscale Circulation Variability from Five years of Quasi-continuous Glider Observations and Numerical Simulation at a Key Sub-basin 'Choke' Point.

NASA Astrophysics Data System (ADS)

Heslop, E. E.; Mourre, B.; Juza, M.; Troupin, C.; Escudier, R.; Torner, M.; Tintore, J.

2016-02-01

Quasi-continuous glider observations over 5 years have uniquely characterised a high frequency variability in the circulation through the Ibiza Channel, an important `choke' point in the Western Mediterranean Sea. This `choke' point governs the basin/sub-basin scale circulation and the north/south exchanges of different water masses. The resulting multi-scale variability impacts the regional shelf and open ocean ecosystems, including the spawning grounds of Atlantic bluefin tuna. Through the unique glider record we show the relevance of the weekly/mesoscale variability, which is of same order as the previously established seasonal and inter-annual variability. To understand the drivers of this variability we combine the glider data with numerical simulations (WMOP) and altimetry. Two key drivers are identified; extreme winter events, which cause the formation of a cold winter mode water (Winter Intermediate Water) in the shelf areas to the north of the Ibiza Channel, and mesoscale activity, which to the north produce channel `blocking' eddies and to the south intermittent and vigorous flows of fresher `Atlantic' waters through the Ibiza Channel. Results from the 2 km resolution WMOP are compared with the high-resolution (2 - 3 km.) glider data, giving insight into model validation across different scales, for both circulation and water masses. There is an emerging consensus that gliders can uniquely access critical time and length scales and in this study gliders complement existing satellite measurements and models, while opening up new capabilities for multidisciplinary, autonomous and high-resolution ocean observation.

Local and Catchment-Scale Water Storage Changes in Northern Benin Deduced from Gravity Monitoring at Various Time-Scales

NASA Astrophysics Data System (ADS)

Hinderer, J.; Hector, B.; Séguis, L.; Descloitres, M.; Cohard, J.; Boy, J.; Calvo, M.; Rosat, S.; Riccardi, U.; Galle, S.

2013-12-01

Water storage changes (WSC) are investigated by the mean of gravity monitoring in Djougou, northern Benin, in the frame of the GHYRAF (Gravity and Hydrology in Africa) project. In this area, WSC are 1) part of the control system for evapotranspiration (ET) processes, a key variable of the West-African monsoon cycle and 2) the state variable for resource management, a critical issue in storage-poor hard rock basement contexts such as in northern Benin. We show the advantages of gravity monitoring for analyzing different processes in the water cycle involved at various time and space scales, using the main gravity sensors available today (FG5 absolute gravimeter, superconducting gravimeter -SG- and CG5 micro-gravimeter). The study area is also part of the long-term observing system AMMA-Catch, and thus under intense hydro-meteorological monitoring (rain, soil moisture, water table level, ET ...). Gravity-derived WSC are compared at all frequencies to hydrological data and to hydrological models calibrated on these data. Discrepancies are analyzed to discuss the pros and cons of each approach. Fast gravity changes (a few hours) are significant when rain events occur, and involve different contributions: rainfall itself, runoff, fast subsurface water redistribution, screening effect of the gravimeter building and local topography. We investigate these effects and present the statistical results of a set of rain events recorded with the SG installed in Djougou since July 2010. The intermediate time scale of gravity changes (a few days) is caused by ET and both vertical and horizontal water redistribution. The integrative nature of gravity measurements does not allow to separate these different contributions, and the screening from the shelter reduces our ability to retrieve ET values. Also, atmospheric corrections are critical at such frequencies, and deserve some specific attention. However, a quick analysis of gravity changes following rain events shows that the values are in accordance with expected ET values (up to about 5mm/day). Seasonal WSC are analyzed since 2008 using FG5 absolute gravity measurements four times a year and since 2010 using the continuous SG time series. They can reach up to 12 microGal (≈270mm) and show a clear interannual variability, as can be expected from rainfall variability in the area. This data set allows some estimates of an average specific yield for the local aquifer, together with a scaling factor for Magnetic Resonance Soundings-derived water content.

Asymmetric variations in the tropical ascending branches of Hadley circulations and the associated mechanisms and effects

NASA Astrophysics Data System (ADS)

Sun, Bo

2018-03-01

This study investigates the variations in the tropical ascending branches (TABs) of Hadley circulations (HCs) during past decades, using a variety of reanalysis datasets. The northern tropical ascending branch (NTAB) and the southern tropical ascending branch (STAB), which are defined as the ascending branches of the Northern Hemisphere HC and Southern Hemisphere HC, respectively, are identified and analyzed regarding their trends and variability. The reanalysis datasets consistently show a persistent increase in STAB during past decades, whereas they show less consistency in NTAB regarding its decadalto multidecadal variability, which generally features a decreasing trend. These asymmetric trends in STAB and NTAB are attributed to asymmetric trends in the tropical SSTs. The relationship between STAB/NTAB and tropical SSTs is further examined regarding their interannual and decadal- to multidecadal variability. On the interannual time scale, the STAB and NTAB are essentially modulated by the eastern-Pacific type of ENSO, with a strengthened (weakened) STAB (NTAB) under an El Niño condition. On the decadal- to multidecadal time scale, the variability of STAB and NTAB is closely related to the southern tropical SSTs and the meridional asymmetry of global tropical SSTs, respectively. The tropical eastern Pacific SSTs (southern tropical SSTs) dominate the tropical SST-NTAB/STAB relationship on the interannual (decadal- to multidecadal) scale, whereas the NTAB is a passive factor in this relationship. Moreover, a cross-hemispheric relationship between the NTAB/STAB and the HC upper-level meridional winds is revealed.

A reference time scale for Site U1385 (Shackleton Site) on the SW Iberian Margin

NASA Astrophysics Data System (ADS)

Hodell, D.; Lourens, L.; Crowhurst, S.; Konijnendijk, T.; Tjallingii, R.; Jiménez-Espejo, F.; Skinner, L.; Tzedakis, P. C.; Abrantes, Fatima; Acton, Gary D.; Alvarez Zarikian, Carlos A.; Bahr, André; Balestra, Barbara; Barranco, Estefanìa Llave; Carrara, Gabriela; Ducassou, Emmanuelle; Flood, Roger D.; Flores, José-Abel; Furota, Satoshi; Grimalt, Joan; Grunert, Patrick; Hernández-Molina, Javier; Kim, Jin Kyoung; Krissek, Lawrence A.; Kuroda, Junichiro; Li, Baohua; Lofi, Johanna; Margari, Vasiliki; Martrat, Belen; Miller, Madeline D.; Nanayama, Futoshi; Nishida, Naohisa; Richter, Carl; Rodrigues, Teresa; Rodríguez-Tovar, Francisco J.; Roque, Ana Cristina Freixo; Sanchez Goñi, Maria F.; Sierro Sánchez, Francisco J.; Singh, Arun D.; Sloss, Craig R.; Stow, Dorrik A. V.; Takashimizu, Yasuhiro; Tzanova, Alexandrina; Voelker, Antje; Xuan, Chuang; Williams, Trevor

2015-10-01

We produced a composite depth scale and chronology for Site U1385 on the SW Iberian Margin. Using log(Ca/Ti) measured by core scanning XRF at 1-cm resolution in all holes, a composite section was constructed to 166.5 meter composite depth (mcd) that corrects for stretching and squeezing in each core. Oxygen isotopes of benthic foraminifera were correlated to a stacked δ18O reference signal (LR04) to produce an oxygen isotope stratigraphy and age model. Variations in sediment color contain very strong precession signals at Site U1385, and the amplitude modulation of these cycles provides a powerful tool for developing an orbitally-tuned age model. We tuned the U1385 record by correlating peaks in L* to the local summer insolation maxima at 37°N. The benthic δ18O record of Site U1385, when placed on the tuned age model, generally agrees with other time scales within their respective chronologic uncertainties. The age model is transferred to down-core data to produce a continuous time series of log(Ca/Ti) that reflect relative changes of biogenic carbonate and detrital sediment. Biogenic carbonate increases during interglacial and interstadial climate states and decreases during glacial and stadial periods. Much of the variance in the log(Ca/Ti) is explained by a linear combination of orbital frequencies (precession, tilt and eccentricity), whereas the residual signal reflects suborbital climate variability. The strong correlation between suborbital log(Ca/Ti) variability and Greenland temperature over the last glacial cycle at Site U1385 suggests that this signal can be used as a proxy for millennial-scale climate variability over the past 1.5 Ma. Millennial climate variability, as expressed by log(Ca/Ti) at Site U1385, was a persistent feature of glacial climates over the past 1.5 Ma, including glacial periods of the early Pleistocene ('41-kyr world') when boundary conditions differed significantly from those of the late Pleistocene ('100-kyr world'). Suborbital variability was suppressed during interglacial stages and enhanced during glacial periods, especially when benthic δ18O surpassed 3.3-3.5‰. Each glacial inception was marked by appearance of strong millennial variability and each deglaciation was preceded by a terminal stadial event. Suborbital variability may be a symptomatic feature of glacial climate or, alternatively, may play a more active role in the inception and/or termination of glacial cycles.

Inherent Variability in Short-time Wind Turbine Statistics from Turbulence Structure in the Atmospheric Surface Layer

NASA Astrophysics Data System (ADS)

Lavely, Adam; Vijayakumar, Ganesh; Brasseur, James; Paterson, Eric; Kinzel, Michael

2011-11-01

Using large-eddy simulation (LES) of the neutral and moderately convective atmospheric boundary layers (NBL, MCBL), we analyze the impact of coherent turbulence structure of the atmospheric surface layer on the short-time statistics that are commonly collected from wind turbines. The incoming winds are conditionally sampled with a filtering and thresholding algorithm into high/low horizontal and vertical velocity fluctuation coherent events. The time scales of these events are ~5 - 20 blade rotations and are roughly twice as long in the MCBL as the NBL. Horizontal velocity events are associated with greater variability in rotor power, lift and blade-bending moment than vertical velocity events. The variability in the industry standard 10 minute average for rotor power, sectional lift and wind velocity had a standard deviation of ~ 5% relative to the ``infinite time'' statistics for the NBL and ~10% for the MCBL. We conclude that turbulence structure associated with atmospheric stability state contributes considerable, quantifiable, variability to wind turbine statistics. Supported by NSF and DOE.

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments in terms of regional and large-scale climate variability during the past.

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.

Orbital time scale and new C-isotope record for Cenomanian-Turonian boundary stratotype

NASA Astrophysics Data System (ADS)

Sageman, Bradley B.; Meyers, Stephen R.; Arthur, Michael A.

2006-02-01

Previous time scales for the Cenomanian-Turonian boundary (CTB) interval containing Oceanic Anoxic Event II (OAE II) vary by a factor of three. In this paper we present a new orbital time scale for the CTB stratotype established independently of radiometric, biostratigraphic, or geochemical data sets, update revisions of CTB biostratigraphic zonation, and provide a new detailed carbon isotopic record for the CTB study interval. The orbital time scale allows an independent assessment of basal biozone ages relative to the new CTB date of 93.55 Ma (GTS04). The δ13Corg data document the abrupt onset of OAE II, significant variability in δ13Corg values, and values enriched to almost -22‰. These new data underscore the difficulty in defining OAE II termination. Using the new isotope curve and time scale, estimates of OAE II duration can be determined and exported to other sites based on integration of well-established chemostratigraphic and biostratigraphic datums. The new data will allow more accurate calculations of biogeochemical and paleobiologic rates across the CTB.

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

High-Frequency Response of the Atmospheric Electric Potential Gradient Under Strong and Dry Boundary-Layer Convection

NASA Astrophysics Data System (ADS)

Conceição, Ricardo; Silva, Hugo Gonçalves; Bennett, Alec; Salgado, Rui; Bortoli, Daniele; Costa, Maria João; Collares Pereira, Manuel

2018-01-01

The spectral response of atmospheric electric potential gradient gives important information about phenomena affecting this gradient at characteristic time scales ranging from years (e.g., solar modulation) to fractions of a second (e.g., turbulence). While long-term time scales have been exhaustively explored, short-term scales have received less attention. At such frequencies, space-charge transport inside the planetary boundary layer becomes a sizeable contribution to the potential gradient variability. For the first time, co-located (Évora, Portugal) measurements of boundary-layer backscatter profiles and the 100-Hz potential gradient are reported. Five campaign days are analyzed, providing evidence for a relation between high-frequency response of the potential gradient and strong dry convection.

Centennial-scale links between Atlantic Ocean dynamics and hydroclimate over the last 4400 years: Insights from the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Thirumalai, K.; Quinn, T. M.; Okumura, Y.; Richey, J. N.; Partin, J. W.; Poore, R. Z.

2015-12-01

Surface circulation in the Atlantic Ocean is an important mediator of global climate and yet its variability is poorly constrained on centennial timescales. Changes in the Atlantic meridional overturning circulation (AMOC) have been implicated in late Holocene climate variability in the Western Hemisphere, although the relationship between AMOC variability and hydroclimate is uncertain due to the lack of sufficiently highly resolved proxy records. Here we present a replicated reconstruction of sea-surface temperature (SST) and salinity (SSS) from the Garrison Basin in the northern Gulf of Mexico (NGOM) spanning the last 4,400 years to better constrain past sea-surface conditions. We generated time series of paired Mg/Ca (SST proxy) and δ18O (SST and SSS proxy) variations in planktic foraminifer Globigerinoides ruber (white variety) from three multi-cores collected in 2010. Using a Monte Carlo-based technique we produce a stacked record from the three multi-cores and constrain analytical, calibration, chronological, and sampling uncertainties. We apply this technique to existing paired Mg/Ca- δ18O studies in the Gulf of Mexico and Atlantic Ocean to facilitate comparison between time-uncertain proxy reconstructions. The Garrison Basin stack exhibits large centennial-scale variability (σSST~0.6°C; δ18Osw~0.17‰) and indicates a substantially cool (0.9±0.5°C) and fresh (0.26±0.1‰) Little Ice Age (LIA; 1450-1850 A.D.), corroborating extant records from the Gulf of Mexico. Focusing on the last millennium, we analyze a suite of oceanic and terrestrial proxy records to demonstrate a centennial-scale link between salt advection in the Atlantic Ocean, a diagnostic parameter of ocean circulation, and hydroclimate in the adjacent continents. The ensuing multiproxy relationships seem to be consistent with spatial field correlations of limited salinity and rainfall instrumental/reanalysis data, which suggest that NGOM salinity varies with large-scale Atlantic Ocean circulation and continental precipitation. Our results imply significant centennial-scale variability over the late Holocene and are consistent with limited observational analysis indicating a slowdown of AMOC during the LIA.

Pore scale study of multiphase multicomponent reactive transport during CO 2 dissolution trapping

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

Chen, Li; Wang, Mengyi; Kang, Qinjun

Solubility trapping is crucial for permanent CO 2 sequestration in deep saline aquifers. For the first time, a pore-scale numerical method is developed to investigate coupled scCO 2-water two-phase flow, multicomponent (CO 2(aq), H +, HCO 3 –, CO 3 2 – and OH –) mass transport, heterogeneous interfacial dissolution reaction, and homogeneous dissociation reactions. Pore-scale details of evolutions of multiphase distributions and concentration fields are presented and discussed. Time evolutions of several variables including averaged CO 2(aq) concentration, scCO 2 saturation, and pH value are analyzed. Specific interfacial length, an important variable which cannot be determined but is requiredmore » by continuum models, is investigated in detail. Mass transport coefficient or efficient dissolution rate is also evaluated. The pore-scale results show strong non-equilibrium characteristics during solubility trapping due to non-uniform distributions of multiphase as well as slow mass transport process. Complicated coupling mechanisms between multiphase flow, mass transport and chemical reactions are also revealed. Lastly, effects of wettability are also studied. The pore-scale studies provide deep understanding of non-linear non-equilibrium multiple physicochemical processes during CO 2 solubility trapping processes, and also allow to quantitatively predict some important empirical relationships, such as saturation-interfacial surface area, for continuum models.« less

Pore scale study of multiphase multicomponent reactive transport during CO 2 dissolution trapping

DOE PAGES

Chen, Li; Wang, Mengyi; Kang, Qinjun; ...

2018-04-26

Solubility trapping is crucial for permanent CO 2 sequestration in deep saline aquifers. For the first time, a pore-scale numerical method is developed to investigate coupled scCO 2-water two-phase flow, multicomponent (CO 2(aq), H +, HCO 3 –, CO 3 2 – and OH –) mass transport, heterogeneous interfacial dissolution reaction, and homogeneous dissociation reactions. Pore-scale details of evolutions of multiphase distributions and concentration fields are presented and discussed. Time evolutions of several variables including averaged CO 2(aq) concentration, scCO 2 saturation, and pH value are analyzed. Specific interfacial length, an important variable which cannot be determined but is requiredmore » by continuum models, is investigated in detail. Mass transport coefficient or efficient dissolution rate is also evaluated. The pore-scale results show strong non-equilibrium characteristics during solubility trapping due to non-uniform distributions of multiphase as well as slow mass transport process. Complicated coupling mechanisms between multiphase flow, mass transport and chemical reactions are also revealed. Lastly, effects of wettability are also studied. The pore-scale studies provide deep understanding of non-linear non-equilibrium multiple physicochemical processes during CO 2 solubility trapping processes, and also allow to quantitatively predict some important empirical relationships, such as saturation-interfacial surface area, for continuum models.« less

Pore scale study of multiphase multicomponent reactive transport during CO2 dissolution trapping

NASA Astrophysics Data System (ADS)

Chen, Li; Wang, Mengyi; Kang, Qinjun; Tao, Wenquan

2018-06-01

Solubility trapping is crucial for permanent CO2 sequestration in deep saline aquifers. For the first time, a pore-scale numerical method is developed to investigate coupled scCO2-water two-phase flow, multicomponent (CO2(aq), H+, HCO3-, CO32- and OH-) mass transport, heterogeneous interfacial dissolution reaction, and homogeneous dissociation reactions. Pore-scale details of evolutions of multiphase distributions and concentration fields are presented and discussed. Time evolutions of several variables including averaged CO2(aq) concentration, scCO2 saturation, and pH value are analyzed. Specific interfacial length, an important variable which cannot be determined but is required by continuum models, is investigated in detail. Mass transport coefficient or efficient dissolution rate is also evaluated. The pore-scale results show strong non-equilibrium characteristics during solubility trapping due to non-uniform distributions of multiphase as well as slow mass transport process. Complicated coupling mechanisms between multiphase flow, mass transport and chemical reactions are also revealed. Finally, effects of wettability are also studied. The pore-scale studies provide deep understanding of non-linear non-equilibrium multiple physicochemical processes during CO2 solubility trapping processes, and also allow to quantitatively predict some important empirical relationships, such as saturation-interfacial surface area, for continuum models.

Variable diffusion in stock market fluctuations

NASA Astrophysics Data System (ADS)

Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.

2015-02-01

We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.

Variable interstellar absorption lines in young stellar aggregates

NASA Astrophysics Data System (ADS)

Krełowski, J.; Strobel, A.; Vješnica, S.; Melekh, D.; Bondar, A.

2018-06-01

The variability of interstellar atomic lines, sporadically reported in the astronomical literature, has been confirmed both in the case of the nearby hot star δ Ori and the very young and violent star-forming region η Carinae, using high-resolution echelle spectra. The presented variability concerns the intensities and profiles of Na I, K I and Ca II. The time-scale of the above-mentioned variations clearly suggests very local phenomena as their cause. It is important to say that not all interstellar lines vary in unison.

A photometric study of the nova-like variable TT Arietis with the MOST satellite

NASA Astrophysics Data System (ADS)

Vogt, N.; Chené, A.-N.; Moffat, A. F. J.; Matthews, J. M.; Kuschnig, R.; Guenther, D. B.; Rowe, J. F.; Rucinski, S. M.; Sasselov, D.; Weiss, W. W.

2013-12-01

Variability on all time scales between seconds and decades is typical for cataclysmic variables (CVs). One of the brightest and best studied CVs is TT Ari, a nova-like variable which belongs to the VY Scl subclass, characterized by occasional low states in their light curves. It is also known as a permanent superhumper at high state, revealing ``positive'' (PS> P0) as well as ``negative'' (PS< P0) superhumps, where PS is the period of the superhump and P0 the orbital period. TT Ari was observed by the Canadian space telescope MOST for about 230 hours nearly continuously in 2007, with a time resolution of 48 seconds. Here we analyze these data, obtaining a dominant ``negative'' superhump signal with a period PS = 0.1331 days and a mean amplitude of 0.09 mag. Strong flickering with amplitudes up to 0.2 mag and peak-to-peak time scales of 15-20 minutes is superimposed on the periodic variations. We found no indications for significant quasi-periodic oscillations with periods around 15 minutes, reported by other authors. We discuss the known superhump behaviour of TT Ari during the last five decades and conclude that our period value is at the upper limit of all hitherto determined ``negative'' superhump periods of TT Ari, before and after the MOST run.

Kinetic energy budgets during the life cycle of intense convective activity

NASA Technical Reports Server (NTRS)

Fuelberg, H. E.; Scoggins, J. R.

1978-01-01

Synoptic-scale data at three- and six-hour intervals are employed to study the relationship between changing kinetic energy variables and the life cycles of two severe squall lines. The kinetic energy budgets indicate a high degree of kinetic energy generation, especially pronounced near the jet-stream level. Energy losses in the storm environment are due to the transfer of kinetic energy from grid to subgrid scales of motion; large-scale upward vertical motion carries aloft the kinetic energy generated by storm activity at lower levels. In general, the time of maximum storm intensity is also the time of maximum energy conversion and transport.

Optimal output fast feedback in two-time scale control of flexible arms

NASA Technical Reports Server (NTRS)

Siciliano, B.; Calise, A. J.; Jonnalagadda, V. R. P.

1986-01-01

Control of lightweight flexible arms moving along predefined paths can be successfully synthesized on the basis of a two-time scale approach. A model following control can be designed for the reduced order slow subsystem. The fast subsystem is a linear system in which the slow variables act as parameters. The flexible fast variables which model the deflections of the arm along the trajectory can be sensed through strain gage measurements. For full state feedback design the derivatives of the deflections need to be estimated. The main contribution of this work is the design of an output feedback controller which includes a fixed order dynamic compensator, based on a recent convergent numerical algorithm for calculating LQ optimal gains. The design procedure is tested by means of simulation results for the one link flexible arm prototype in the laboratory.

Event Horizon Telescope observations as probes for quantum structure of astrophysical black holes

NASA Astrophysics Data System (ADS)

Giddings, Steven B.; Psaltis, Dimitrios

2018-04-01

The need for a consistent quantum evolution for black holes has led to proposals that their semiclassical description is modified not just near the singularity, but at horizon or larger scales. If such modifications extend beyond the horizon, they influence regions accessible to distant observation. Natural candidates for these modifications behave like metric fluctuations, with characteristic length scales and timescales set by the horizon radius. We investigate the possibility of using the Event Horizon Telescope to observe these effects, if they have a strength sufficient to make quantum evolution consistent with unitarity, without introducing new scales. We find that such quantum fluctuations can introduce a strong time dependence for the shape and size of the shadow that a black hole casts on its surrounding emission. For the black hole in the center of the Milky Way, detecting the rapid time variability of its shadow will require nonimaging timing techniques. However, for the much larger black hole in the center of the M87 galaxy, a variable black-hole shadow, if present with these parameters, would be readily observable in the individual snapshots that will be obtained by the Event Horizon Telescope.

Exploratory analysis of rainfall events in Coimbra, Portugal: variability of raindrop characteristics

NASA Astrophysics Data System (ADS)

Carvalho, S. C. P.; de Lima, M. I. P.; de Lima, J. L. M. P.

2012-04-01

Laser disdrometers can monitor efficiently rainfall characteristics at small temporal scales, providing data on rain intensity, raindrop diameter and fall speed, and raindrop counts over time. This type of data allows for the increased understanding of the rainfall structure at small time scales. Of particular interest for many hydrological applications is the characterization of the properties of extreme events, including the intra-event variability, which are affected by different factors (e.g. geographical location, rainfall generating mechanisms). These properties depend on the microphysical, dynamical and kinetic processes that interact to produce rain. In this study we explore rainfall data obtained during two years with a laser disdrometer installed in the city of Coimbra, in the centre region of mainland Portugal. The equipment was developed by Thies Clima. The data temporal resolution is one-minute. Descriptive statistics of time series of raindrop diameter (D), fall speed, kinetic energy, and rain rate were studied at the event scale; for different variables, the average, maximum, minimum, median, variance, standard deviation, quartile, coefficient of variation, skewness and kurtosis were determined. The empirical raindrop size distribution, N(D), was also calculated. Additionally, the parameterization of rainfall was attempted by investigating the applicability of different theoretical statistical distributions to fit the empirical data (e.g. exponential, gamma and lognormal distributions). As expected, preliminary results show that rainfall properties and structure vary with rainfall type and weather conditions over the year. Although only two years were investigated, already some insight into different rain events' structure was obtained.

Transient coupling relationships of the Holocene Australian monsoon

NASA Astrophysics Data System (ADS)

McRobie, F. H.; Stemler, T.; Wyrwoll, K.-H.

2015-08-01

The northwest Australian summer monsoon owes a notable degree of its interannual variability to interactions with other regional monsoon systems. Therefore, changes in the nature of these relationships may contribute to variability in monsoon strength over longer time scales. Previous attempts to evaluate how proxy records from the Indonesian-Australian monsoon region correspond to other records from the Indian and East Asian monsoon regions, as well as to El Niño-related proxy records, have been qualitative, relying on 'curve-fitting' methods. Here, we seek a quantitative approach for identifying coupling relationships between paleoclimate proxy records, employing statistical techniques to compute the interdependence of two paleoclimate time series. We verify the use of complex networks to identify coupling relationships between modern climate indices. This method is then extended to a set of paleoclimate proxy records from the Asian, Australasian and South American regions spanning the past 9000 years. The resulting networks demonstrate the existence of coupling relationships between regional monsoon systems on millennial time scales, but also highlight the transient nature of teleconnections during this period. In the context of the northwest Australian summer monsoon, we recognise a shift in coupling relationships from strong interhemispheric links with East Asian and ITCZ-related proxy records in the mid-Holocene to significantly weaker coupling in the later Holocene. Although the identified links cannot explain the underlying physical processes leading to coupling between regional monsoon systems, this method provides a step towards understanding the role that changes in teleconnections play in millennial-to orbital-scale climate variability.

Characterizing spatial and temporal variability in methane gas-flux dynamics of subtropical wetlands in the Big Cypress National Preserve, Florida

NASA Astrophysics Data System (ADS)

Sirianni, M.; Comas, X.; Shoemaker, B.

2017-12-01

Wetland methane emissions are highly variable both in space and time, and are controlled by changes in certain biogeochemical controls (i.e. organic matter availability; redox potential) and/or other environmental factors (i.e. soil temperature; water level). Consequently, hot spots (areas with disproportionally high emissions) may develop where biogeochemical and environmental conditions are especially conducive for enhancing certain microbial processes such as methanogenesis. The Big Cypress National Preserve is a collection of subtropical wetlands in southwestern Florida, including extensive forested (cypress, pine, hardwood) and sawgrass ecosystems that dry and flood annually in response to rainfall. In addition to rainfall, hydroperiod, fire regime, elevation above mean sea level, dominant vegetation type and underlying geological controls contribute to the development and evolution of organic and calcitic soils found throughout the Preserve. Currently, the U.S. Geological Survey employs eddy covariance methods within the Preserve to quantify carbon and methane exchanges over several spatially extensive vegetation communities. While eddy covariance towers are a convenient tool for measuring gas exchanges at the ecosystem scale, their spatially extensive footprint (hundreds of meters) may mask smaller scale spatial variabilities that may be conducive to the development of hot spots. Similarly, temporal resolution (i.e. sampling effort) at scales smaller that the eddy covariance measurement footprint is important since low resolution data may overlook rapid emission events and the temporal variability of discrete hot spots. In this work, we intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a unique combination of ground penetrating radar (GPR), capacitance probes, gas traps, and time-lapse photography. By using an array of methods that vary in spatio-temporal resolution, we hope to better understand the uncertainties associated with measuring wetland methane fluxes across different spatial and temporal scales. Our results have implications for characterizing and refining methane flux estimates in subtropical peat soils that could be used for climate models.

Dissolved organic nitrogen dynamics in the North Sea: A time series analysis (1995-2005)

NASA Astrophysics Data System (ADS)

Van Engeland, T.; Soetaert, K.; Knuijt, A.; Laane, R. W. P. M.; Middelburg, J. J.

2010-09-01

Dissolved organic nitrogen (DON) dynamics in the North Sea was explored by means of long-term time series of nitrogen parameters from the Dutch national monitoring program. Generally, the data quality was good with little missing data points. Different imputation methods were used to verify the robustness of the patterns against these missing data. No long-term trends in DON concentrations were found over the sampling period (1995-2005). Inter-annual variability in the different time series showed both common and station-specific behavior. The stations could be divided into two regions, based on absolute concentrations and the dominant times scales of variability. Average DON concentrations were 11 μmol l -1 in the coastal region and 5 μmol l -1 in the open sea. Organic fractions of total dissolved nitrogen (TDN) averaged 38 and 71% in the coastal zone and open sea, respectively, but increased over time due to decreasing dissolved inorganic nitrogen (DIN) concentrations. In both regions intra-annual variability dominated over inter-annual variability, but DON variation in the open sea was markedly shifted towards shorter time scales relative to coastal stations. In the coastal zone a consistent seasonal DON cycle existed with high values in spring-summer and low values in autumn-winter. In the open sea seasonality was weak. A marked shift in the seasonality was found at the Dogger Bank, with DON accumulation towards summer and low values in winter prior to 1999, and accumulation in spring and decline throughout summer after 1999. This study clearly shows that DON is a dynamic actor in the North Sea and should be monitored systematically to enable us to understand fully the functioning of this ecosystem.

Assessing the catchment's filtering effect on the propagation of meteorological anomalies

NASA Astrophysics Data System (ADS)

di Domenico, Antonella; Laguardia, Giovanni; Margiotta, Maria Rosaria

2010-05-01

The characteristics of drought propagation within a catchment are evaluated by means of the analysis of time series of water fluxes and storages' states. The study area is the Agri basin, Southern Italy, closed at the Tarangelo gauging station (507 km2). Once calibrated the IRP weather generator (Veneziano and Iacobellis, 2002) on observed data, a 100 years time series of precipitation has been produced. The drought statistics obtained from the synthetic data have been compared to the ones obtained from the limited observations available. The DREAM hydrological model has been calibrated based on observed precipitation and discharge. From the model run on the synthetic precipitation we have obtained the time series of variables relevant for assessing the status of the catchment, namely total runoff and its components, actual evapotranspiration, and soil moisture. The Standardized Precipitation Index (SPI; McKee et al., 1993) has been calculated for different averaging periods. The modelled data have been processed for the calculation of drought indices. In particular, we have chosen to use their transformation into standardized variables. We have performed autocorrelation analysis for assessing the characteristic time scales of the variables. Moreover, we have investigated through cross correlation their relationships, assessing also the SPI averaging period for which the maximum correlation is reached. The variables' drought statistics, namely number of events, duration, and deficit volumes, have been assessed. As a result of the filtering effect exerted by the different catchment storages, the characteristic time scale and the maximum correlation SPI averaging periods for the different time series tend to increase. Thus, the number of drought events tends to decrease and their duration to increase under increasing storage.

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

Unravelling connections between river flow and large-scale climate: experiences from Europe

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Kingston, D. G.; Lavers, D.; Stagge, J. H.; Tallaksen, L. M.

2016-12-01

The United Nations has identified better knowledge of large-scale water cycle processes as essential for socio-economic development and global water-food-energy security. In this context, and given the ever-growing concerns about climate change/ variability and human impacts on hydrology, there is an urgent research need: (a) to quantify space-time variability in regional river flow, and (b) to improve hydroclimatological understanding of climate-flow connections as a basis for identifying current and future water-related issues. In this paper, we draw together studies undertaken at the pan-European scale: (1) to evaluate current methods for assessing space-time dynamics for different streamflow metrics (annual regimes, low flows and high flows) and for linking flow variability to atmospheric drivers (circulation indices, air-masses, gridded climate fields and vapour flux); and (2) to propose a plan for future research connecting streamflow and the atmospheric conditions in Europe and elsewhere. We believe this research makes a useful, unique contribution to the literature through a systematic inter-comparison of different streamflow metrics and atmospheric descriptors. In our findings, we highlight the need to consider appropriate atmospheric descriptors (dependent on the target flow metric and region of interest) and to develop analytical techniques that best characterise connections in the ocean-atmosphere-land surface process chain. We call for the need to consider not only atmospheric interactions, but also the role of the river basin-scale terrestrial hydrological processes in modifying the climate signal response of river flows.

Dispersal kernels and their drivers captured with a hydrodynamic model and spatial indices: A case study on anchovy ( Engraulis encrasicolus) early life stages in the Bay of Biscay

NASA Astrophysics Data System (ADS)

Huret, M.; Petitgas, P.; Woillez, M.

2010-10-01

Dispersal of fish early life stages explains part of the recruitment success, through interannual variability in spawning, transport and survival. Dispersal results from a complex interaction between physical and biological processes acting at different temporal and spatial scales, and at the individual or population level. In this paper we quantify the response of anchovy egg and larval dispersal in the Bay of Biscay to the following sources of variability: vertical larval behaviour, drift duration, adult spawning location and timing, and spatio-temporal variability in the hydrodynamics. We use simulations of Lagrangian trajectories in a 3-dimensional hydrodynamic model, as well as spatial indices describing different properties of the dispersal kernel: the mean transport (distance, direction), its variance, occupation of space by particles and their aggregation. We show that larval drift duration has a major impact on the dispersion at scales of ˜100 km, but that vertical behaviour becomes dominant reducing dispersion at scales of ˜1-10 km. Spawning location plays a major role in explaining connectivity patterns, in conjunction with spawning temporal variability. Interannual variability in the circulation dominates over seasonal variability. However, seasonal patterns become predominant for coastal spawning locations, revealing a recurrent shift in the direction of dispersal during the anchovy spawning season.

Model for the techno-economic analysis of common work of wind power and CCGT power plant to offer constant level of power in the electricity market

NASA Astrophysics Data System (ADS)

Tomsic, Z.; Rajsl, I.; Filipovic, M.

2017-11-01

Wind power varies over time, mainly under the influence of meteorological fluctuations. The variations occur on all time scales. Understanding these variations and their predictability is of key importance for the integration and optimal utilization of wind in the power system. There are two major attributes of variable generation that notably impact the participation on power exchanges: Variability (the output of variable generation changes and resulting in fluctuations in the plant output on all time scales) and Uncertainty (the magnitude and timing of variable generation output is less predictable, wind power output has low levels of predictability). Because of these variability and uncertainty wind plants cannot participate to electricity market, especially to power exchanges. For this purpose, the paper presents techno-economic analysis of work of wind plants together with combined cycle gas turbine (CCGT) plant as support for offering continues power to electricity market. A model of wind farms and CCGT plant was developed in program PLEXOS based on real hourly input data and all characteristics of CCGT with especial analysis of techno-economic characteristics of different types of starts and stops of the plant. The Model analyzes the followings: costs of different start-stop characteristics (hot, warm, cold start-ups and shutdowns) and part load performance of CCGT. Besides the costs, the technical restrictions were considered such as start-up time depending on outage duration, minimum operation time, and minimum load or peaking capability. For calculation purposes, the following parameters are necessary to know in order to be able to economically evaluate changes in the start-up process: ramp up and down rate, time of start time reduction, fuel mass flow during start, electricity production during start, variable cost of start-up process, cost and charges for life time consumption for each start and start type, remuneration during start up time regarding expected or unexpected starts, the cost and revenues for balancing energy (important when participating in electricity market), and the cost or revenues for CO2-certificates. Main motivation for this analysis is to investigate possibilities to participate on power exchanges by offering continues guarantied power from wind plants by backing-up them with CCGT power plant.

Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

NASA Astrophysics Data System (ADS)

Hadi, Sinan Jasim; Tombul, Mustafa

2018-06-01

Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion of several scales in which seasonality and irregularity can be captured. Using hydrological and meteorological variables also improved the ability to forecast the streamflow.

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

NASA Astrophysics Data System (ADS)

Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

(abstract) Short Time Period Variations in Jupiter's Synchrotron Radiation

NASA Technical Reports Server (NTRS)

Bolton, S. J.; Klein, M. J.; Gulkis, S.; Foster, R.; Heiles, C.; Pater, I. de

1994-01-01

The long term time variability of Jupiter's synchrotron radiation on yearly time scales has been established for some time. For many years, theorists have speculated about the effects variations in the solar wind, solar flux, Io, the Io torus, and Jupiter's magnetic field have on the ultra-relativistic electron population responsible for the emission. Early observational results suggested the additional possibility of a short term time variability, on timescales of days to weeks. In 1989 a program designed to investigate the existence of short term time variability using the 85 foot Hat Creek radio telescope operating at 1400 MHz was initiated. The availability of a dedicated telescope provided the opportunity, for the first time, to obtain numerous observations over the full Jupiter rotation period. These and future observations will enable two important studies, characterization and confirmation of possible short term variations, and the investigation of the stability of Jupiter's synchrotron emission beaming curve. Analysis of Hat Creek observations and early results from the Maryland Point Naval research Laboratory will be presented.

Relationships between convective storms and their environment in AVE IV determined from a three-dimensional subsynoptic-scale, trajectory model

NASA Technical Reports Server (NTRS)

Wilson, G. S.

1977-01-01

The paper describes interrelationships between synoptic-scale and convective-scale systems obtained by following individual air parcels as they traveled within the convective storm environment of AVE IV. (NASA's fourth Atmospheric Variability Experiment, AVE IV, was a 36-hour study in April 1975 of the atmospheric variability and structure in regions of convective storms.) A three-dimensional trajectory model was used to calculate parcel paths, and manually digitized radar was employed to locate convective activity of various intensities and to determine those trajectories that traversed the storm environment. Spatial and temporal interrelationships are demonstrated by reference to selected time periods of AVE IV which contain the development and movement of the squall line in which the Neosho tornado was created.

Creative use of pilot points to address site and regional scale heterogeneity in a variable-density model

USGS Publications Warehouse

Dausman, Alyssa M.; Doherty, John; Langevin, Christian D.

2010-01-01

Pilot points for parameter estimation were creatively used to address heterogeneity at both the well field and regional scales in a variable-density groundwater flow and solute transport model designed to test multiple hypotheses for upward migration of fresh effluent injected into a highly transmissive saline carbonate aquifer. Two sets of pilot points were used within in multiple model layers, with one set of inner pilot points (totaling 158) having high spatial density to represent hydraulic conductivity at the site, while a second set of outer points (totaling 36) of lower spatial density was used to represent hydraulic conductivity further from the site. Use of a lower spatial density outside the site allowed (1) the total number of pilot points to be reduced while maintaining flexibility to accommodate heterogeneity at different scales, and (2) development of a model with greater areal extent in order to simulate proper boundary conditions that have a limited effect on the area of interest. The parameters associated with the inner pilot points were log transformed hydraulic conductivity multipliers of the conductivity field obtained by interpolation from outer pilot points. The use of this dual inner-outer scale parameterization (with inner parameters constituting multipliers for outer parameters) allowed smooth transition of hydraulic conductivity from the site scale, where greater spatial variability of hydraulic properties exists, to the regional scale where less spatial variability was necessary for model calibration. While the model is highly parameterized to accommodate potential aquifer heterogeneity, the total number of pilot points is kept at a minimum to enable reasonable calibration run times.

Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

Regional and sediment depth differences in nematode community structure greater than between habitats on the New Zealand margin: Implications for vulnerability to anthropogenic disturbance

NASA Astrophysics Data System (ADS)

Rosli, Norliana; Leduc, Daniel; Rowden, Ashley A.; Probert, P. Keith; Clark, Malcolm R.

2018-01-01

Deep-sea community attributes vary at a range of spatial scales. However, identifying the scale at which environmental factors affect variability in deep-sea communities remains difficult, as few studies have been designed in such a way as to allow meaningful comparisons across more than two spatial scales. In the present study, we investigated nematode diversity, community structure and trophic structure at different spatial scales (sediment depth (cm), habitat (seamount, canyon, continental slope; 1-100 km), and geographic region (100-10000 km)), while accounting for the effects of water depth, in two regions on New Zealand's continental margin. The greatest variability in community attributes was found between sediment depth layers and between regions, which explained 2-4 times more variability than habitats. The effect of habitat was consistently stronger in the Hikurangi Margin than the Bay of Plenty for all community attributes, whereas the opposite pattern was found in the Bay of Plenty where effect of sediment depth was greater in Bay of Plenty. The different patterns at each scale in each region reflect the differences in the environmental variables between regions that control nematode community attributes. Analyses suggest that nematode communities are mostly influenced by sediment characteristics and food availability, but that disturbance (fishing activity and bioturbation) also accounts for some of the observed patterns. The results provide new insight on the relative importance of processes operating at different spatial scales in regulating nematode communities in the deep-sea, and indicate potential differences in vulnerability to anthropogenic disturbance.

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.

Scaling laws for perturbations in the ocean-atmosphere system following large CO2 emissions

NASA Astrophysics Data System (ADS)

Towles, N.; Olson, P.; Gnanadesikan, A.

2015-01-01

Scaling relationships are derived for the perturbations to atmosphere and ocean variables from large transient CO2 emissions. Using the carbon cycle model LOSCAR (Zeebe et al., 2009; Zeebe, 2012b) we calculate perturbations to atmosphere temperature and total carbon, ocean temperature, total ocean carbon, pH, and alkalinity, marine sediment carbon, plus carbon-13 isotope anomalies in the ocean and atmosphere resulting from idealized CO2 emission events. The peak perturbations in the atmosphere and ocean variables are then fit to power law functions of the form γDαEbeta, where D is the event duration, E is its total carbon emission, and γ is a coefficient. Good power law fits are obtained for most system variables for E up to 50 000 PgC and D up to 100 kyr. However, these power laws deviate substantially from predictions based on simplified equilibrium considerations. For example, although all of the peak perturbations increase with emission rate E/D, we find no evidence of emission rate-only scaling α + β =0, a prediction of the long-term equilibrium between CO2 input by volcanism and CO2 removal by silicate weathering. Instead, our scaling yields α + β ≃ 1 for total ocean and atmosphere carbon and 0< α + β < 1 for most of the other system variables. The deviations in these scaling laws from equilibrium predictions are mainly due to the multitude and diversity of time scales that govern the exchange of carbon between marine sediments, the ocean, and the atmosphere.

Hydrologic index development and application to selected Coastwide Reference Monitoring System sites and Coastal Wetlands Planning, Protection and Restoration Act projects

USGS Publications Warehouse

Snedden, Gregg A.; Swenson, Erick M.

2012-01-01

Hourly time-series salinity and water-level data are collected at all stations within the Coastwide Reference Monitoring System (CRMS) network across coastal Louisiana. These data, in addition to vegetation and soils data collected as part of CRMS, are used to develop a suite of metrics and indices to assess wetland condition in coastal Louisiana. This document addresses the primary objectives of the CRMS hydrologic analytical team, which were to (1) adopt standard time-series analytical techniques that could effectively assess spatial and temporal variability in hydrologic characteristics across the Louisiana coastal zone on site, project, basin, and coastwide scales and (2) develop and apply an index based on wetland hydrology that can describe the suitability of local hydrology in the context of maximizing the productivity of wetland plant communities. Approaches to quantifying tidal variability (least squares harmonic analysis) and partitioning variability of time-series data to various time scales (spectral analysis) are presented. The relation between marsh elevation and the tidal frame of a given hydrograph is described. A hydrologic index that integrates water-level and salinity data, which are collected hourly, with vegetation data that are collected annually is developed. To demonstrate its utility, the hydrologic index is applied to 173 CRMS sites across the coast, and variability in index scores across marsh vegetation types (fresh, intermediate, brackish, and saline) is assessed. The index is also applied to 11 sites located in three Coastal Wetlands Planning, Protection and Restoration Act projects, and the ability of the index to convey temporal hydrologic variability in response to climatic stressors and restoration measures, as well as the effect that this community may have on wetland plant productivity, is illustrated.

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.

Finite-Size Scaling Analysis of Binary Stochastic Processes and Universality Classes of Information Cascade Phase Transition

NASA Astrophysics Data System (ADS)

Mori, Shintaro; Hisakado, Masato

2015-05-01

We propose a finite-size scaling analysis method for binary stochastic processes X(t) in { 0,1} based on the second moment correlation length ξ for the autocorrelation function C(t). The purpose is to clarify the critical properties and provide a new data analysis method for information cascades. As a simple model to represent the different behaviors of subjects in information cascade experiments, we assume that X(t) is a mixture of an independent random variable that takes 1 with probability q and a random variable that depends on the ratio z of the variables taking 1 among recent r variables. We consider two types of the probability f(z) that the latter takes 1: (i) analog [f(z) = z] and (ii) digital [f(z) = θ(z - 1/2)]. We study the universal functions of scaling for ξ and the integrated correlation time τ. For finite r, C(t) decays exponentially as a function of t, and there is only one stable renormalization group (RG) fixed point. In the limit r to ∞ , where X(t) depends on all the previous variables, C(t) in model (i) obeys a power law, and the system becomes scale invariant. In model (ii) with q ≠ 1/2, there are two stable RG fixed points, which correspond to the ordered and disordered phases of the information cascade phase transition with the critical exponents β = 1 and ν|| = 2.

Challenges to Progress in Studies of Climate-Tectonic-Erosion Interactions

NASA Astrophysics Data System (ADS)

Burbank, D. W.

2016-12-01

Attempts to unravel the relative importance of climate and tectonics in modulating topography and erosion should compare relevant data sets at comparable temporal and spatial scales. Given that such data are uncommonly available, how can we compare diverse data sets in a robust fashion? Many erosion-rate studies rely on detrital cosmogenic nuclides. What time scales can such data address, and what landscape conditions do they require to provide accurate representations of long-term erosion rates? To what extent do large-scale, but infrequent erosional events impact long-term rates? Commonly, long-term erosion rates are deduced from thermochronologic data. What types of data are needed to test for consistency of rates across a given interval or change in rates through time? Similarly, spatial and temporal variability in precipitation or tectonics requires averaging across appropriate scales. How are such data obtained in deforming mountain belts, and how do we assess their reliability? This study describes the character and temporal duration of key variables that are needed to examine climate-tectonic-erosion interactions, explores the strengths and weaknesses of several study areas, and suggests the types of data requirements that will underpin enlightening "tests" of hypotheses related to the mutual impacts of climate, tectonics, and erosion.

Evaluating the performance of different predictor strategies in regression-based downscaling with a focus on glacierized mountain environments

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Nemec, Johanna

2016-04-01

This study presents first steps towards verifying the hypothesis that uncertainty in global and regional glacier mass simulations can be reduced considerably by reducing the uncertainty in the high-resolution atmospheric input data. To this aim, we systematically explore the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in geo-environmentally and climatologically very distinct settings, all within highly complex topography and in the close proximity to mountain glaciers: (1) the Vernagtbach station in the Northern European Alps (VERNAGT), (2) the Artesonraju measuring site in the tropical South American Andes (ARTESON), and (3) the Brewster measuring site in the Southern Alps of New Zealand (BREWSTER). As the large-scale predictors, ERA interim reanalysis data are used. In the applied downscaling model training and evaluation procedures, particular emphasis is put on appropriately accounting for the pitfalls of limited and/or patchy observation records that are usually the only (if at all) available data from the glacierized mountain sites. Generalized linear models and beta regression are investigated as alternatives to ordinary least squares regression for the non-Gaussian target variables. By analyzing results for the three different sites, five predictands and for different times of the year, we look for systematic improvements in the downscaling models' skill specifically obtained by (i) using predictor data at the optimum scale rather than the minimum scale of the reanalysis data, (ii) identifying the optimum predictor allocation in the vertical, and (iii) considering multiple (variable, level and/or grid point) predictor options combined with state-of-art empirical feature selection tools. First results show that in particular for air temperature, those downscaling models based on direct predictor selection show comparative skill like those models based on multiple predictors. For all other target variables, however, multiple predictor approaches can considerably outperform those models based on single predictors. Including multiple variable types emerges as the most promising predictor option (in particular for wind speed at all sites), even if the same predictor set is used across the different cases.

Investigating connections between local-remote atmospheric variability and Greenland outlet glacier behavior

NASA Astrophysics Data System (ADS)

Sobolowski, Stefan; Chen, Linling; Miles, Victoria

2016-04-01

The outlet glaciers along the margins of the Greenland Ice Sheet (GrIS) exhibit a range of behaviors, which are crucial for understanding GrIS mass changes from a dynamical point of view. However, the drivers of this behavior are still poorly understood. Arguments (counter-arguments) have been made for a strong (weak) local oceanic influence on marine terminating outlet glaciers while decadal-scale drivers linked to fluctuations in the Ice sheet itself and the North Atlantic ocean (e.g. Atlantic Multidecadal Variability) have also been posited as drivers. Recently there have also been studies linking (e.g. seasonal to interannual) atmospheric variability, synoptic activity and the Ice Sheet variability. But these studies typically investigate atmospheric links to the large-scale behavior of the Ice Sheet itself and do not go down to the scale of the outlet glaciers. Conversely, investigations of the outlet glaciers often do not include potential links to non-local atmospheric dynamics. Here the authors attempt to bridge the gap and investigate the relationship between atmospheric variability across a range of scales and the behavior of three outlet glaciers on Greenland's southeast coast over a 33-year period (1980-2012). The glaciers - Helheim, Midgard and Fenris - are near Tasiilaq, are marine terminating and exhibit varying degree of connection to the GrIS. ERA-Interim reanalysis, sea-ice data and glacier observations are used for the investigation. Long records of mass balance are unavailable for these glaciers and front position is employed as a measure of glacier atmosphere interactions across multiple scales, as it exhibits robust relationships to atmospheric variability on time scales of seasons to many years, with the strongest relationships seen at seasonal - interannual time scales. The authors do not make the argument that front position is a suitable proxy for mass balance, only that it is indicative of the role of local and remote atmospheric/climate dynamics in glacier behavior. Our study suggests a strong relationship between large-scale tropospheric circulation patterns, such as the so-called Greenland Blocking Index (GBI), and glacier front position. This relationship is seen in the wintertime (summertime) circulation influence on spring (fall) front position. Dynamically, a physical pathway is illustrated via canonical correlation analyses and composites of low-mid level winds, which show strong southerly advection into the region when the GBI is positive. There are also potential links between local and remote diabatic heating in the atmospheric column, SSTs, sea-ice concentration and front position. Whether there are physical pathways connecting remote surface processes, such as heating along western Greenland is not yet clear. Causality is always difficult to infer in reanalysis-based studies but physical intuition and theory provide multiple lines of evidence, which suggest a substantial influence of large-scale atmospheric dynamics at the margins of the GrIS. Improving our understanding of these physical connections will be crucial, as we know the outlet glaciers will respond under rapidly changing climate conditions.

A Cutoff in the X-Ray Fluctuation Power Density Spectrum of the Seyfert 1 Galaxy NGC 3516

NASA Technical Reports Server (NTRS)

Edelson, Rick; Nandra, Kirpal

1999-01-01

During 1997 March-July, RXTE observed the bright, strongly variable Seyfert 1 galaxy NGC 3516 once every approx. 12.8 hr for 4.5 months and nearly continuously (with interruptions due to SAA passage but not Earth occultation) for a 4.2 day period in the middle. These were followed by ongoing monitoring once every approx. 4.3 days. These data are used to construct the first well-determined X-ray fluctuation power density spectrum (PDS) of an active galaxy to span more than 4 decades of usable temporal frequency. The PDS shows no signs of any strict or quasi-periodicity, but does show a progressive flattening of the power-low slope from -1.74 at short time scales to -0.73 at longer time scales. This is the clearest observation to date of the long-predicted cutoff in the PDS. The characteristic variability time scale corresponding to this cutoff temporal frequency is approx. 1 month. Although it is unclear how this time scale may be interpreted in terms of a physical size or process, there are several promising candidate models. The PDS appears similar to those seen for Galactic black hole candidates such as Cyg X-1, suggesting that these two classes of objects with very different luminosities and putative black hole masses (differing by more than a factor of 10(exp 5)) may have similar X-ray generation processes and structures.

A new reference frame for astronomically-tuned Plio-Pleistocene climate variability derived from a benthic oxygen isotope splice of the Mediterranean

NASA Astrophysics Data System (ADS)

Lourens, L. J.; Ziegler, M.; Konijnendijk, T. Y. M.; Hilgen, F. J.; Bos, R.; Beekvelt, B.; van Loevezijn, A.; Collin, S.

2017-12-01

The astronomical theory of climate has revolutionized our understanding of past climate change and the development of highly accurate geologic time scales for the entire Cenozoic. Most of this understanding has come from the construction of astronomically tuned global ocean benthic foraminiferal oxygen isotope (δ18O) stacked record, derived by the international drilling operations of DSDP, ODP and IODP. The tuning includes fixed phase relationships between the obliquity and precession cycles and the inferred high-latitude climate, i.e. glacial-interglacial, response, which hark back to SPECMAP, using simple ice sheet models and a limited number of radiometric dates. This approach was largely implemented in the widely applied LR04 stack, though LR04 assumed shorter response times for the smaller ice caps during the Pliocene. In the past decades, an astronomically calibrated time scale for the Pliocene and Pleistocene of the Mediterranean has been developed, which has become the reference for the standard Geologic Time Scale. Typical of the Mediterranean marine sediments are the cyclic lithological alternations, reflecting the interference between obliquity and precession-paced low latitude climate variability, such as the African monsoon. Here we present the first benthic foraminiferal based oxygen isotope record of the Mediterranean reference scale, which strikingly mirrors the LR04. We will use this record to discuss the assumed open ocean glacial-interglacial related phase relations over the past 5.3 million years.

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.

Variability of tropical cyclone rapid intensification in the North Atlantic and its relationship with climate variations

NASA Astrophysics Data System (ADS)

Wang, Chunzai; Wang, Xidong; Weisberg, Robert H.; Black, Michael L.

2017-12-01

The paper uses observational data from 1950 to 2014 to investigate rapid intensification (RI) variability of tropical cyclones (TCs) in the North Atlantic and its relationships with large-scale climate variations. RI is defined as a TC intensity increase of at least 15.4 m/s (30 knots) in 24 h. The seasonal RI distribution follows the seasonal TC distribution, with the highest number in September. Although an RI event can occur anywhere over the tropical North Atlantic (TNA), there are three regions of maximum RI occurrence: (1) the western TNA of 12°N-18°N and 60°W-45°W, (2) the Gulf of Mexico and the western Caribbean Sea, and (3) the open ocean southeast and east of Florida. RI events also show a minimum value in the eastern Caribbean Sea north of South America—a place called a hurricane graveyard due to atmospheric divergence and subsidence. On longer time scales, RI displays both interannual and multidecadal variability, but RI does not show a long-term trend due to global warming. The top three climate indices showing high correlations with RI are the June-November ENSO and Atlantic warm pool indices, and the January-March North Atlantic oscillation index. It is found that variabilities of vertical wind shear and TC heat potential are important for TC RI in the hurricane main development region, whereas relative humidity at 500 hPa is the main factor responsible for TC RI in the eastern TNA. However, the large-scale oceanic and atmospheric variables analyzed in this study do not show an important role in TC RI in the Gulf of Mexico and the open ocean southeast and east of Florida. This suggests that other factors such as small-scale changes of oceanic and atmospheric variables or TC internal processes may be responsible for TC RI in these two regions. Additionally, the analyses indicate that large-scale atmospheric and oceanic variables are not critical to TC genesis and formation; however, once a tropical depression forms, large-scale climate variations play a role in TC intensification.

Records of millennial-scale climate change from the Great Basin of the Western United States

NASA Astrophysics Data System (ADS)

Benson, Larry

High-resolution (decadal) records of climate change from the Owens, Mono, and Pyramid Lake basins of California and Nevada indicate that millennialscale oscillations in climate of the Great Basin occurred between 52.6 and 9.2 14C ka. Climate records from the Owens and Pyramid Lake basins indicate that most, but not all, glacier advances (stades) between 52.6 and ˜15.0 14C ka occurred during relatively dry times. During the last alpine glacial period (˜60.0 to ˜14.0 14C ka), stadial/interstadial oscillations were recorded in Owens and Pyramid Lake sediments by the negative response of phytoplankton productivity to the influx of glacially derived silicates. During glacier advances, rock flour diluted the TOC fraction of lake sediments and introduction of glacially derived suspended sediment also increased the turbidity of lake water, decreasing light penetration and photosynthetic production of organic carbon. It is not possible to correlate objectively peaks in the Owens and Pyramid Lake TOC records (interstades) with Dansgaard-Oeschger interstades in the GISP2 ice-core δ18O record given uncertainties in age control and difference in the shapes of the OL90, PLC92 and GISP2 records. In the North Atlantic region, some climate records have clearly defined variability/cyclicity with periodicities of 102 to 103 yr; these records are correlatable over several thousand km. In the Great Basin, climate proxies also have clearly defined variability with similar time constants, but the distance over which this variability can be correlated remains unknown. Globally, there may be minimal spatial scales (domains) within which climate varies coherently on centennial and millennial scales, but it is likely that the sizes of these domains vary with geographic setting and time. A more comprehensive understanding of the mechanisms of climate forcing and the physical linkages between climate forcing and system response is needed in order to predict the spatial scale(s) over which climate varies coherently.

The relation between face-emotion recognition and social function in adolescents with autism spectrum disorders: A case control study.

PubMed

Høyland, Anne Lise; Nærland, Terje; Engstrøm, Morten; Lydersen, Stian; Andreassen, Ole Andreas

2017-01-01

An altered processing of emotions may contribute to a reduced ability for social interaction and communication in autism spectrum disorder, ASD. We investigated how face-emotion recognition in ASD is different from typically developing across adolescent age groups. Fifty adolescents diagnosed with ASD and 49 typically developing (age 12-21 years) were included. The ASD diagnosis was underpinned by parent-rated Social Communication Questionnaire. We used a cued GO/ NOGO task with pictures of facial expressions and recorded reaction time, intra-individual variability of reaction time and omissions/commissions. The Social Responsiveness Scale was used as a measure of social function. Analyses were conducted for the whole group and for young (< 16 years) and old (≥ 16 years) age groups. We found no significant differences in any task measures between the whole group of typically developing and ASD and no significant correlations with the Social Responsiveness Scale. However, there was a non-significant tendency for longer reaction time in the young group with ASD (p = 0.099). The Social Responsiveness Scale correlated positively with reaction time (r = 0.30, p = 0.032) and intra-individual variability in reaction time (r = 0.29, p = 0.037) in the young group and in contrast, negatively in the old group (r = -0.23, p = 0.13; r = -0.38, p = 0.011, respectively) giving significant age group interactions for both reaction time (p = 0.008) and intra-individual variability in reaction time (p = 0.001). Our findings suggest an age-dependent association between emotion recognition and severity of social problems indicating a delayed development of emotional understanding in ASD. It also points towards alterations in top-down attention control in the ASD group. This suggests novel disease-related features that should be investigated in more details in experimental settings.

Decadal variability on the Northwest European continental shelf

NASA Astrophysics Data System (ADS)

Jones, Sam; Cottier, Finlo; Inall, Mark; Griffiths, Colin

2018-02-01

Decadal scale time series of the shelf seas are important for understanding both climate and process studies. Despite numerous investigations of long-term temperature variability in the shelf seas, studies of salinity variability are few. Salt is a more conservative tracer than temperature in shallow seas, and it can reveal changes in local hydrographic conditions as well as transmitted basin-scale changes. Here, new inter-annual salinity time series on the northwest European shelf are developed and a 13 year high resolution salinity record from a coastal mooring in western Scotland is presented and analysed. We find strong temporal variability in coastal salinity on timescales ranging from tidal to inter-annual, with the magnitude of variability greatest during winter months. There is little seasonality and no significant decadal trend in the coastal time series of salinity. We propose 4 hydrographic states to explain salinity variance in the shelf area west of Scotland based on the interaction between a baroclinic coastal current and wind-forced barotropic flow: while wind forcing is important, we find that changes in the buoyancy-driven flow are more likely to influence long-term salinity observations. We calculate that during prevailing westerly wind conditions, surface waters in the Sea of the Hebrides receive a mix of 62% Atlantic origin water to 38% coastal sources. This contrasts with easterly wind conditions, during which the mix is 6% Atlantic to 94% coastal sources on average. This 'switching' between hydrographic states is expected to impact nutrient transport and therefore modify the level of primary productivity on the shelf. This strong local variability in salinity is roughly an order of magnitude greater than changes in the adjacent ocean basin, and we infer from this that Scottish coastal waters are likely to be resilient to decadal changes in ocean climate.

Time-Lapse Geophysical Measurements targeting Spatial and Temporal Variability in Biogenic Gas Production from Peat Soils in a Hydrologically Controlled Wetland in the Florida Everglades

NASA Astrophysics Data System (ADS)

Wright, W. J.; Shahan, T.; Sharp, N.; Comas, X.

2015-12-01

Peat soils are known to release globally significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. However, uncertainties still remain regarding the spatio-temporal distribution of gas accumulations and triggering mechanisms of gas releasing events. Furthermore, most research on peatland gas dynamics has traditionally been focused on high latitude peatlands. Therefore, understanding gas dynamics in low-latitude peatlands (e.g. the Florida Everglades) is key to global climate research. Recent studies in the Everglades have demonstrated that biogenic gas flux values may vary when considering different temporal and spatial scales of measurements. The work presented here targets spatial variability in gas production and release at the plot scale in an approximately 85 m2 area, and targets temporal variability with data collected during the spring months of two different years. This study is located in the Loxahatchee Impoundment Landscape Assessment (LILA), a hydrologically controlled, landscape scale (30 Ha) model of the Florida Everglades. Ground penetrating radar (GPR) has been used in the past to investigate biogenic gas dynamics in peat soils, and is used in this study to monitor changes of in situ gas storage. Each year, a grid of GPR profiles was collected to image changes in gas distribution in 2d on a weekly basis, and several flux chambers outfitted with time-lapse cameras captured high resolution (hourly) gas flux measurements inside the GPR grid. Combining these methods allows us to use a mass balance approach to estimate spatial variability in gas production rates, and capture temporal variability in gas flux rates.

The Predictability of Large-Scale, Short-Period Variability in the Philippine Sea and the Influence of Such Variability on Long-Range acoustic Propagation

DTIC Science & Technology

2015-03-31

with the black line indicating an average of these travel times. Altimetry data from 2000- 2007 were used to obtain the predictions, hence the...Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison, D.E. & Stammer , D., Eds., ESA Publication WPP-306. Dushaw, B. D., P. F. Worcester

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

PubMed

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

2012-05-01

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

Drivers of Intra-Summer Seasonality and Daily Variability of Coastal Low Cloudiness in California Subregions

NASA Astrophysics Data System (ADS)

Schwartz, R. E.; Iacobellis, S.; Gershunov, A.; Williams, P.; Cayan, D. R.

2014-12-01

Summertime low cloud intrusion into the terrestrial west coast of North America impacts human, ecological, and logistical systems. Over a broad region of the West Coast, summer (May - September) coastal low cloudiness (CLC) varies coherently on interannual to interdecadal timescales and has been found to be organized by North Pacific sea surface temperature. Broad-scale studies of low stratiform cloudiness over ocean basins also find that the season of maximum low stratus corresponds to the season of maximum lower tropospheric stability (LTS) or estimated inversion strength. We utilize a 18-summer record of CLC derived from NASA/NOAA Geostationary Operational Environmental Satellite (GOES) at 4km resolution over California (CA) to make a more nuanced spatial and temporal examination of intra-summer variability in CLC and its drivers. We find that uniform spatial coherency over CA is not apparent for intra-summer variability in CLC. On monthly to daily timescales, at least two distinct subregions of coastal California (CA) can be identified, where relationships between meteorology and stratus variability appear to change throughout summer in each subregion. While north of Point Conception and offshore the timing of maximum CLC is closely coincident with maximum LTS, in the Southern CA Bight and northern Baja region, maximum CLC occurs up to about a month before maximum LTS. It appears that summertime CLC in this southern region is not as strongly related as in the northern region to LTS. In particular, although the relationship is strong in May and June, starting in July the daily relationship between LTS and CLC in the south begins to deteriorate. Preliminary results indicate a moderate association between decreased CLC in the south and increased precipitable water content above 850 hPa on daily time scales beginning in July. Relationships between daily CLC variability and meteorological variables including winds, inland temperatures, relative humidity, and geopotential heights within and above the marine boundary layer are investigated and dissected by month, CA subregion, and cloud height. The rich spatial detail of the satellite derived CLC record is utilized to examine the propagation in time and space of CLC on synoptic scales within and among subregions.

A Blind Survey for AGN in the Kepler Field through Optical Variability

NASA Astrophysics Data System (ADS)

Olling, Robert; Shaya, E. J.; Mushotzky, R.

2013-01-01

We present an initial analysis of three quarters of Kepler LLC time series of 400 small galaxies. The Kepler LLC data is sampled about twice per hour, and allows us to investigate variability on time scales between about one day and one month. The calibrated Kepler LLC light curves still contain many instrumental effects that can not be taken out in a robust manner. Instead, our analysis relies on the similarity of variability measures in the three independent quarters to decide if an galaxy shows variability, or not. We estimate that roughly 15% of our small galaxies shows variability at levels exceeding several parts per thousand (mmag) on timescales of days to weeks. However, this estimate is probably uncertain by a factor of two. Our data is more sensitive by several factors of ten as compared to extant data sets.

Day-to-Day Variability of Postural Sway and Its Association With Cognitive Function in Older Adults: A Pilot Study

PubMed Central

Leach, Julia M.; Mancini, Martina; Kaye, Jeffrey A.; Hayes, Tamara L.; Horak, Fay B.

2018-01-01

Introduction: Increased variability in motor function has been observed during the initial stages of cognitive decline. However, the natural variability of postural control, as well as its association with cognitive status and decline, remains unknown. The objective of this pilot study was to characterize the day-to-day variability in postural sway in non-demented older adults. We hypothesized that older adults with a lower cognitive status would have higher day-to-day variability in postural sway. Materials and Methods: A Nintendo Wii balance board (WBB) was used to quantify postural sway in the home twice daily for 30 days in 20 non-demented, community-dwelling older adults: once under a single-task condition and once under a dual-task condition (using a daily word search task administered via a Nook tablet). Mean sway distance, velocity, area, centroidal frequency and frequency dispersion were derived from the center of pressure data acquired from the WBB. Results: Linear relationships were observed between the day-to-day variability in postural sway and cognitive status (indexed by cognitive global z-scores). More variability in time-domain postural sway (sway distance and area) and less variability in frequency-domain postural sway (centroidal sway frequency) were associated with a lower cognitive status under both the single- and dual-task conditions. Additionally, lower cognitive performance rates on the daily word search task were related to a lower cognitive status. Discussion: This small pilot study conducted on a short time scale motivates large-scale implementations over more extended time periods. Tracking longitudinal changes in postural sway may further our understanding of early-stage postural decline and its association with cognitive decline and, in turn, may aid in the early detection of dementia during preclinical stages when the utility of disease-modifying therapies would be greatest. PMID:29780319

Day-to-Day Variability of Postural Sway and Its Association With Cognitive Function in Older Adults: A Pilot Study.

PubMed

Leach, Julia M; Mancini, Martina; Kaye, Jeffrey A; Hayes, Tamara L; Horak, Fay B

2018-01-01

Introduction : Increased variability in motor function has been observed during the initial stages of cognitive decline. However, the natural variability of postural control, as well as its association with cognitive status and decline, remains unknown. The objective of this pilot study was to characterize the day-to-day variability in postural sway in non-demented older adults. We hypothesized that older adults with a lower cognitive status would have higher day-to-day variability in postural sway. Materials and Methods : A Nintendo Wii balance board (WBB) was used to quantify postural sway in the home twice daily for 30 days in 20 non-demented, community-dwelling older adults: once under a single-task condition and once under a dual-task condition (using a daily word search task administered via a Nook tablet). Mean sway distance, velocity, area, centroidal frequency and frequency dispersion were derived from the center of pressure data acquired from the WBB. Results : Linear relationships were observed between the day-to-day variability in postural sway and cognitive status (indexed by cognitive global z-scores). More variability in time-domain postural sway (sway distance and area) and less variability in frequency-domain postural sway (centroidal sway frequency) were associated with a lower cognitive status under both the single- and dual-task conditions. Additionally, lower cognitive performance rates on the daily word search task were related to a lower cognitive status. Discussion : This small pilot study conducted on a short time scale motivates large-scale implementations over more extended time periods. Tracking longitudinal changes in postural sway may further our understanding of early-stage postural decline and its association with cognitive decline and, in turn, may aid in the early detection of dementia during preclinical stages when the utility of disease-modifying therapies would be greatest.

Dynamic and Regression Modeling of Ocean Variability in the Tide-Gauge Record at Seasonal and Longer Periods

NASA Technical Reports Server (NTRS)

Hill, Emma M.; Ponte, Rui M.; Davis, James L.

2007-01-01

Comparison of monthly mean tide-gauge time series to corresponding model time series based on a static inverted barometer (IB) for pressure-driven fluctuations and a ocean general circulation model (OM) reveals that the combined model successfully reproduces seasonal and interannual changes in relative sea level at many stations. Removal of the OM and IB from the tide-gauge record produces residual time series with a mean global variance reduction of 53%. The OM is mis-scaled for certain regions, and 68% of the residual time series contain a significant seasonal variability after removal of the OM and IB from the tide-gauge data. Including OM admittance parameters and seasonal coefficients in a regression model for each station, with IB also removed, produces residual time series with mean global variance reduction of 71%. Examination of the regional improvement in variance caused by scaling the OM, including seasonal terms, or both, indicates weakness in the model at predicting sea-level variation for constricted ocean regions. The model is particularly effective at reproducing sea-level variation for stations in North America, Europe, and Japan. The RMS residual for many stations in these areas is 25-35 mm. The production of "cleaner" tide-gauge time series, with oceanographic variability removed, is important for future analysis of nonsecular and regionally differing sea-level variations. Understanding the ocean model's strengths and weaknesses will allow for future improvements of the model.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

NASA Astrophysics Data System (ADS)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Elevational characteristics of the archaeal community in full-scale activated sludge wastewater treatment plants at a 3,660-meter elevational scale.

PubMed

Niu, Lihua; Zhang, Xue; Li, Yi; Wang, Peifang; Zhang, Wenlong; Wang, Chao; Wang, Qing

2017-07-01

Due to the important roles of archaea in wastewater treatment processes, archaeal communities have been studied extensively in various anaerobic reactors, but the knowledge of archaeal communities in full-scale activated sludge wastewater treatment plants (WWTPs) remains quite poor. In this study, 454-pyrosequencing was for the first time employed to investigate archaeal communities from 20 full-scale activated sludge WWTPs distributed at a 3,660-meter elevational scale in China. Results showed that archaeal communities from WWTPs were dominated by Methanosarcinales (84.6%). A core archaeal population (94.5%) composed of Methanosaeta, Methanosarcina, Methanogenium and Methanobrevibacter was shared among WWTPs. The elevational pattern of archaeal communities was observed in WWTPs, with an elevational threshold associated with archaeal community richness and structures at approximately 1,500 meters above sea level (masl). A declining trend in community richness with increasing elevation was observed at higher elevations, whereas no trend was presented at lower elevations. Spearman correlation analysis indicated that the archaeal community richness at higher elevations was associated with more environmental variables than that at lower elevations. Redundancy analysis indicated that wastewater variables were the dominant contributors to the variation of community structures at higher elevations, followed by operational variables and elevation.

Turbulent mixing and removal of ozone within an Amazon rainforest canopy

NASA Astrophysics Data System (ADS)

Freire, L. S.; Gerken, T.; Ruiz-Plancarte, J.; Wei, D.; Fuentes, J. D.; Katul, G. G.; Dias, N. L.; Acevedo, O. C.; Chamecki, M.

2017-03-01

Simultaneous profiles of turbulence statistics and mean ozone mixing ratio are used to establish a relation between eddy diffusivity and ozone mixing within the Amazon forest. A one-dimensional diffusion model is proposed and used to infer mixing time scales from the eddy diffusivity profiles. Data and model results indicate that during daytime conditions, the upper (lower) half of the canopy is well (partially) mixed most of the time and that most of the vertical extent of the forest can be mixed in less than an hour. During nighttime, most of the canopy is predominantly poorly mixed, except for periods with bursts of intermittent turbulence. Even though turbulence is faster than chemistry during daytime, both processes have comparable time scales in the lower canopy layers during nighttime conditions. Nonchemical loss time scales (associated with stomatal uptake and dry deposition) for the entire forest are comparable to turbulent mixing time scale in the lower canopy during the day and in the entire canopy during the night, indicating a tight coupling between turbulent transport and dry deposition and stomatal uptake processes. Because of the significant time of day and height variability of the turbulent mixing time scale inside the canopy, it is important to take it into account when studying chemical and biophysical processes happening in the forest environment. The method proposed here to estimate turbulent mixing time scales is a reliable alternative to currently used models, especially for situations in which the vertical distribution of the time scale is relevant.

Inflammatory cytokine response and reduced heart rate variability in newborns with hypoxic-ischemic encephalopathy.

PubMed

Al-Shargabi, T; Govindan, R B; Dave, R; Metzler, M; Wang, Y; du Plessis, A; Massaro, A N

2017-06-01

To determine whether systemic inflammation-modulating cytokine expression is related to heart rate variability (HRV) in newborns with hypoxic-ischemic encephalopathy (HIE). The data from 30 newborns with HIE were analyzed. Cytokine levels (IL-2, IL-4, IL-6, IL-8, IL-10, IL-13, IL-1β, TNF-α, IFN-λ) were measured either at 24 h of cooling (n=5), 72 h of cooling (n=4) or at both timepoints (n=21). The following HRV metrics were quantified in the time domain: alpha_S, alpha_L, root mean square (RMS) at short time scales (RMS_S), RMS at long time scales (RMS_L), while low-frequency power (LF) and high-frequency power (HF) were quantified in the frequency domain. The relationships between HRV metrics and cytokines were evaluated using mixed-models. IL-6, IL-8, IL-10, and IL-13 levels were inversely related to selected HRV metrics. Inflammation-modulating cytokines may be important mediators in the autonomic dysfunction observed in newborns with HIE.

Direct measurement of sub-surface mass change using the variable-baseline gravity gradient method

USGS Publications Warehouse

Kennedy, Jeffrey; Ferré, Ty P.A.; Güntner, Andreas; Abe, Maiko; Creutzfeldt, Benjamin

2014-01-01

Time-lapse gravity data provide a direct, non-destructive method to monitor mass changes at scales from cm to km. But, the effectively infinite spatial sensitivity of gravity measurements can make it difficult to isolate the signal of interest. The variable-baseline gravity gradient method, based on the difference of measurements between two gravimeters, is an alternative to the conventional approach of individually modeling all sources of mass and elevation change. This approach can improve the signal-to-noise ratio for many applications by removing the contributions of Earth tides, loading, and other signals that have the same effect on both gravimeters. At the same time, this approach can focus the support volume within a relatively small user-defined region of the subsurface. The method is demonstrated using paired superconducting gravimeters to make for the first time a large-scale, non-invasive measurement of infiltration wetting front velocity and change in water content above the wetting front.

Nonlinear zero-sum differential game analysis by singular perturbation methods

NASA Technical Reports Server (NTRS)

Sinar, J.; Farber, N.

1982-01-01

A class of nonlinear, zero-sum differential games, exhibiting time-scale separation properties, can be analyzed by singular-perturbation techniques. The merits of such an analysis, leading to an approximate game solution, as well as the 'well-posedness' of the formulation, are discussed. This approach is shown to be attractive for investigating pursuit-evasion problems; the original multidimensional differential game is decomposed to a 'simple pursuit' (free-stream) game and two independent (boundary-layer) optimal-control problems. Using multiple time-scale boundary-layer models results in a pair of uniformly valid zero-order composite feedback strategies. The dependence of suboptimal strategies on relative geometry and own-state measurements is demonstrated by a three dimensional, constant-speed example. For game analysis with realistic vehicle dynamics, the technique of forced singular perturbations and a variable modeling approach is proposed. Accuracy of the analysis is evaluated by comparison with the numerical solution of a time-optimal, variable-speed 'game of two cars' in the horizontal plane.

Sole larval supply to coastal nurseries: Interannual variability and connectivity at interregional and interpopulation scales

NASA Astrophysics Data System (ADS)

Savina, M.; Lunghi, M.; Archambault, B.; Baulier, L.; Huret, M.; Le Pape, O.

2016-05-01

Simulating fish larval drift helps assess the sensitivity of recruitment variability to early life history. An individual-based model (IBM) coupled to a hydrodynamic model was used to simulate common sole larval supply from spawning areas to coastal and estuarine nursery grounds at the meta-population scale (4 assessed stocks), from the southern North Sea to the Bay of Biscay (Western Europe) on a 26-yr time series, from 1982 to 2007. The IBM allowed each particle released to be transported by currents, to grow depending on temperature, to migrate vertically depending on development stage, to die along pelagic stages or to settle on a nursery, representing the life history from spawning to metamorphosis. The model outputs were analysed to explore interannual patterns in the amounts of settled sole larvae at the population scale; they suggested: (i) a low connectivity between populations at the larval stage, (ii) a moderate influence of interannual variation in the spawning biomass, (iii) dramatic consequences of life history on the abundance of settling larvae and (iv) the effects of climate variability on the interannual variability of the larvae settlement success.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

The chaotic long-term X-ray variability of 4U 1705-44

NASA Astrophysics Data System (ADS)

Phillipson, R. A.; Boyd, P. T.; Smale, A. P.

2018-07-01

The low-mass X-ray binary 4U1705-44 exhibits dramatic long-term X-ray time variability with a time-scale of several hundred days. The All-Sky Monitor (ASM) aboard the Rossi X-ray Timing Explorer (RXTE) and the Japanese Monitor of All-sky X-ray Image (MAXI) aboard the International Space Station together have continuously observed the source from 1995 December through 2014 May. The combined ASM-MAXI data provide a continuous time series over 50 times the length of the time-scale of interest. Topological analysis can help us identify `fingerprints' in the phase space of a system unique to its equations of motion. The Birman-Williams theorem postulates that if such fingerprints are the same between two systems, then their equations of motion must be closely related. The phase-space embedding of the source light curve shows a strong resemblance to the double-welled non-linear Duffing oscillator. We explore a range of parameters for which the Duffing oscillator closely mirrors the time evolution of 4U1705-44. We extract low period, unstable periodic orbits from the 4U1705-44 and Duffing time series and compare their topological information. The Duffing and 4U1705-44 topological properties are identical, providing strong evidence that they share the same underlying template. This suggests that we can look to the Duffing equation to help guide the development of a physical model to describe the long-term X-ray variability of this and other similarly behaved X-ray binary systems.

Biogeochemical Response to Mesoscale Physical Forcing in the California Current System

NASA Technical Reports Server (NTRS)

Niiler, Pearn P.; Letelier, Ricardo; Moisan, John R.; Marra, John A. (Technical Monitor)

2001-01-01

In the first part of the project, we investigated the local response of the coastal ocean ecosystems (changes in chlorophyll, concentration and chlorophyll, fluorescence quantum yield) to physical forcing by developing and deploying Autonomous Drifting Ocean Stations (ADOS) within several mesoscale features along the U.S. west coast. Also, we compared the temporal and spatial variability registered by sensors mounted in the drifters to that registered by the sensors mounted in the satellites in order to assess the scales of variability that are not resolved by the ocean color satellite. The second part of the project used the existing WOCE SVP Surface Lagrangian drifters to track individual water parcels through time. The individual drifter tracks were used to generate multivariate time series by interpolating/extracting the biological and physical data fields retrieved by remote sensors (ocean color, SST, wind speed and direction, wind stress curl, and sea level topography). The individual time series of the physical data (AVHRR, TOPEX, NCEP) were analyzed against the ocean color (SeaWiFS) time-series to determine the time scale of biological response to the physical forcing. The results from this part of the research is being used to compare the decorrelation scales of chlorophyll from a Lagrangian and Eulerian framework. The results from both parts of this research augmented the necessary time series data needed to investigate the interactions between the ocean mesoscale features, wind, and the biogeochemical processes. Using the historical Lagrangian data sets, we have completed a comparison of the decorrelation scales in both the Eulerian and Lagrangian reference frame for the SeaWiFS data set. We are continuing to investigate how these results might be used in objective mapping efforts.

Here Be Dragons: Effective (X-ray) Timing with the Cospectrum

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela; Bachetti, Matteo

2018-01-01

In recent years, the cross spectrum has received considerable attention as a means of characterising the variability of astronomical sources as a function of wavelength. While much has been written about the statistics of time and phase lags, the cospectrum—the real part of the cross spectrum—has only recently been understood as means of mitigating instrumental effects dependent on temporal frequency in astronomical detectors, as well as a method of characterizing the coherent variability in two wavelength ranges on different time scales. In this talk, I will present recent advances made in understanding the statistical properties of cospectra, leading to much improved inferences for periodic and quasi-periodic signals. I will also present a new method to reliably mitigate instrumental effects such as dead time in X-ray detectors, and show how we can use the cospectrum to model highly variable sources such as X-ray binaries or Active Galactic Nuclei.

Toward Characterizing the 4D Structure of Precipitation at the Headwater Catchment Scale in Mountainous Regions

NASA Astrophysics Data System (ADS)

Barros, A. P.; Prat, O. P.; Sun, X.; Shrestha, P.; Miller, D.

2009-04-01

The classic conceptual model of orographic rainfall depicts strong stationary horizontal gradients in rainfall accumulations and landcover contrasts across topographic divides (i.e. the rainshadow) at the broad scale of mountain ranges, or isolated orographic features. Whereas this model is sufficient to fingerprint the land-modulation of precipitation at the macroscale in climate studies, and can be useful to force geological models of land evolution for example, it fails to describe the active 4D space-time gradients that are critical at the fundamental scale of mountain hydrometeorology and hydrology, that is the headwater catchment. That is, the scale at which flash-floods are generated and landslides are triggered. Our work surveying the spatial and temporal habits of clouds and rainfall for some of the world's major mountain ranges from remotely-sensed data shows a close alignment of spatial scaling behavior with landform down to the mountain fold scale, that is the ridge-valley. Likewise, we find that diurnal and seasonal cycles are organized and constrained by topography from the macro- to the meso- to the alpha-scale of individual basins varying with synoptic weather conditions. At the catchment scale, the diurnal cycle exhibits an oscillatory behavior with storm features moving up and down from the ridge crests to the valley floor and back and forth from head to mouth along the valley with strong variations in rainfall intensity and duration. Direct observations to provide quantitative estimates of precipitation at this scale are beyond the capability of satellite-based observations present and anticipated in the next 10-20 years. This limitation can be addressed by assimilating the space-time modes of variability of rainfall into satellite-observations at coarser scale using multiscale blending algorithms. The challenge is to characterize the modes of space-time variability of precipitation in a systematic, and quantitative fashion that can be generalized. It requires understanding the physical controls that govern the diurnal cycle and how these physical controls translate into spatial and temporal variability of dynamics and microphysics of precipitation in headwater catchments, and especially in the context of extreme events for natural hazards assessments. Toward this goal, we have initiated a sequence of number of intense observing period (IOP) campaigns in the Great Smoky Mountains National Park using radiosondes, tethersondes, microrain radars, and a high resolution raingauge network that for the first time monitors rainfall systematically along ridges in the Appalachians. Along with field observations, a high-resolution coupled model has been implemented to diagnose the evolution of the 4D structure of regional circulations and associated precipitation for IOP conditions and for reconstructing historical extremes associated with the interaction of tropical cyclones with the mountains. A synthesis of data analysis and model simulations will be presented.

The Orbital Period of the Classical Nova V458 Vul

NASA Astrophysics Data System (ADS)

Goranskij, V. P.; Metlova, N. V.; Barsukova, E. A.; Burenkov, A. N.; Soloviev, V. Ya.

2008-07-01

Classical nova V458 Vul (N Vul 2007 No.1) was detected as a supersoft X-ray source (SSS) by the Swift XRT several times in the time range between 2007 October 18 and 2008 June 18 (J. Drake et al., ATel #1246 and #1603). Our V photometry shows the plateau in the light curve continued since January till June 2008. This feature accompanies usually the SSS phases in some classical novae. The fragmentary monitoring during plateau shows night- to-night variability with the amplitudes between 1.2 and 0.4 mag and rapid variability by 0.1 mag in the time scale of an hour.

Data and code for the exploratory data analysis of the electrical energy demand in the time domain in Greece.

PubMed

Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

2017-08-01

We present data and code for visualizing the electrical energy data and weather-, climate-related and socioeconomic variables in the time domain in Greece. The electrical energy data include hourly demand, weekly-ahead forecasted values of the demand provided by the Greek Independent Power Transmission Operator and pricing values in Greece. We also present the daily temperature in Athens and the Gross Domestic Product of Greece. The code combines the data to a single report, which includes all visualizations with combinations of all variables in multiple time scales. The data and code were used in Tyralis et al. (2017) [1].

Asynchrony of wind and hydropower resources in Australia.

PubMed

Gunturu, Udaya Bhaskar; Hallgren, Willow

2017-08-18

Wind and hydropower together constitute nearly 80% of the renewable capacity in Australia and their resources are collocated. We show that wind and hydro generation capacity factors covary negatively at the interannual time scales. Thus, the technology diversity mitigates the variability of renewable power generation at the interannual scales. The asynchrony of wind and hydropower resources is explained by the differential impact of the two modes of the El Ni˜no Southern Oscillation - canonical and Modoki - on the wind and hydro resources. Also, the Modoki El Ni˜no and the Modoki La Ni˜na phases have greater impact. The seasonal impact patterns corroborate these results. As the proportion of wind power increases in Australia's energy mix, this negative covariation has implications for storage capacity of excess wind generation at short time scales and for generation system adequacy at the longer time scales.

Multiscale equation-free algorithms for molecular dynamics

NASA Astrophysics Data System (ADS)

Abi Mansour, Andrew

Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

Imaging the Subsurface of the Thuringian Basin (Germany) on Different Spatial Scales

NASA Astrophysics Data System (ADS)

Goepel, A.; Krause, M.; Methe, P.; Kukowski, N.

2014-12-01

Understanding the coupled dynamics of near surface and deep fluid flow patterns is essential to characterize the properties of sedimentary basins, to identify the processes of compaction, diagenesis, and transport of mass and energy. The multidisciplinary project INFLUINS (Integrated FLUid dynamics IN Sedimentary basins) aims for investigating the behavior of fluids in the Thuringian Basin, a small intra-continental sedimentary basin in Germany, at different spatial scales, ranging from the pore scale to the extent of the entire basin. As hydraulic properties often significantly vary with spatial scales, e.g. seismic data using different frequencies are required to gain information about the spatial variability of elastic and hydraulic subsurface properties. For the Thuringian Basin, we use seismic and borehole data acquired in the framework of INFLUINS. Basin-wide structural imaging data are available from 2D reflection seismic profiles as well as 2.5D and 3D seismic travel time tomography. Further, core material from a 1,179 m deep drill hole completed in 2013 is available for laboratory seismic experiments on mm- to cm-scale. The data are complemented with logging data along the entire drill hole. This campaign yielded e.g. sonic and density logs allowing the estimation of in-situ P-velocity and acoustic impedance with a spatial resolution on the cm-scale and provides improved information about petrologic and stratigraphic variability at different scales. Joint interpretation of basin scale structural and elastic properties data with laboratory scale data from ultrasound experiments using core samples enables a detailed and realistic imaging of the subsurface properties on different spatial scales. Combining seismic travel time tomography with stratigraphic interpretation provides useful information of variations in the elastic properties for certain geological units and therefore gives indications for changes in hydraulic properties.

Trend and variability in western and central Africa streamflow, and major drivers of variability between 1950 and 2005

NASA Astrophysics Data System (ADS)

Dieppois, B.; Sidibe, M.; Mahe, G. M.; Paturel, J. E.; Anifowose, B. A.; Lawler, D.; Amoussou, E.

2017-12-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s, triggered many studies investigating rainfall variability and its impacts on water resources and food production systems. However, most studies were focused at the catchment scale. In this study, we aim at investigating the key large-scale controls determining and modulating climate-river flows relationships at the subcontinental scale between 1950 and 2005. Using the first complete monthly streamflow data set (1950-2005) over western and central Africa, streamflow trend and variability are seasonally assessed at this subcontinental scale and compared to those observed in other hydroclimatic variables (precipitation, temperature and potential evapotranspiration). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. In particular, the recent post-1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In addition, the time-evolution of river flows is shown to be primarily driven by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow, as determined using multi-temporal trend and continuous wavelet analysis. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns (such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and the Pacific Decadal Oscillation), which are together modulating the West African monsoon. Furthermore, influences of the catchment properties (e.g. size, vegetation and land use cover, soil properties, direction of stream flow across climate zones) on these decadal fluctuations in river flows have been examined. This study therefore aims to improve the ability of current global to regional climate models to simulate such ranges of variability and understand regional hydroclimate, as a means for improving the development of future scenarios for water resources in western and central Africa.

Predicting Positive Outcomes for Students with Emotional Disturbance

ERIC Educational Resources Information Center

Nickerson, Amanda B.; Brosof, Amy M.; Shapiro, Valerie B.

2004-01-01

This longitudinal study assessed changes in skills for students with emotional disturbance (ED) over a one-year time period in a private special education school and examined variables that predicted positive outcomes for these students. At Time 1, teachers rated 84 students with ED using standardized behavior rating scales to assess problem…

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

Price, Bronwyn; McAlpine, Clive A; Kutt, Alex S; Ward, Doug; Phinn, Stuart R; Ludwig, John A

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

Price, Bronwyn; McAlpine, Clive A.; Kutt, Alex S.; Ward, Doug; Phinn, Stuart R.; Ludwig, John A.

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1–100 ha) and landscape (100–1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes. PMID:24066138

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.

Evidence for a possible modern and mid-Holocene solar influence on climate from Lake Titicaca, South America

NASA Astrophysics Data System (ADS)

Theissen, K. M.; Dunbar, R. B.

2005-12-01

In tropical regions, there are few paleoclimate archives with the necessary resolution to investigate climate variability at interannual-to-decadal timescales prior to the onset of the instrumental record. Interannual variability associated with the El Niño Southern Oscillation (ENSO) is well documented in the instrumental record and the importance of the precessional forcing of millennial variability has been established in studies of tropical paleoclimate records. In contrast, decade-to-century variability is still poorly understood. Here, we examine interannual to decadal variability in the northern Altiplano of South America using digital image analysis of a floating interval of varved sediments of middle Holocene age (~6160-6310 yr BP) from Lake Titicaca. Multi-taper method (MTM) and wavelet frequency-domain analyses were performed on a time series generated from a gray-scaled digital image of the mm-thick laminations. Our results indicate significant power at a decadal periodicity (10-12 years) associated with the Schwabe cycle of solar activity. Frequency-domain analysis also indicates power at 2-2.5 year periodicities associated with ENSO. Similarly, spectral analysis of a 75 year instrumental record of Titicaca lake level shows significant power at both solar and ENSO periodicities. Although both of the examined records are short, our results imply that during both the mid-Holocene and modern times, solar and ENSO variability may have contributed to high frequency climate fluctuations over the northern Altiplano. We suspect that solar influence on large-scale atmospheric circulation features may account for the decadal variability in the mid-Holocene and present-day water balance of the Altiplano.

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Small scale currents and ocean wave heights: from today's models to future satellite observations with CFOSAT and SKIM

NASA Astrophysics Data System (ADS)

Ardhuin, Fabrice; Gille, Sarah; Menemenlis, Dimitris; Rocha, Cesar; Rascle, Nicolas; Gula, Jonathan; Chapron, Bertrand

2017-04-01

Tidal currents and large oceanic currents, such as the Agulhas, Gulf Stream and Kuroshio, are known to modify ocean wave properties, causing extreme sea states that are a hazard to navigation. Recent advances in the understanding and modeling capability of ocean currents at scales of 10 km or less have revealed the ubiquitous presence of fronts and filaments. Based on realistic numerical models, we show that these structures can be the main source of variability in significant wave heights at scales less than 200 km, including important variations at 10 km. This current-induced variability creates gradients in wave heights that were previously overlooked and are relevant for extreme wave heights and remote sensing. The spectrum of significant wave heights is found to be of the order of 70⟨Hs ⟩2/(g2⟨Tm0,-1⟩2) times the current spectrum, where ⟨Hs ⟩ is the spatially-averaged significant wave height, ⟨Tm0,-1⟩ is the average energy period, and g is the gravity acceleration. This small scale variability is consistent with Jason-3 and SARAL along-track variability. We will discuss how future satellite mission with wave spectrometers can help observe these wave-current interactions. CFOSAT is due for launch in 2018, and SKIM is a proposal for ESA Earth Explorer 9.

Characterization of the Spatio-temporal Evolution of the Energy of Recent Tsunamis in Chile and its Connection with the Seismic Source and Geomorphological Conditions

NASA Astrophysics Data System (ADS)

Quiroz, M.; Cienfuegos, R.

2017-12-01

At present, there is good knowledge acquired by the scientific community on characterizing the evolution of tsunami energy at ocean and shelf scales. For instance, the investigations of Rabinovich (2013) and Yamazaki (2011), represent some important advances in this subject. In the present paper we rather focus on tsunami energy evolution, and ultimately its decay, in coastal areas because characteristic time scales of this process has implications for early warning, evacuation initiation, and cancelling. We address the tsunami energy evolution analysis at three different spatial scales, a global scale at the ocean basin level, in particular the Pacific Ocean basin, a regional scale comprising processes that occur at the continental shelf level, and finally a local scale comprising coastal areas or bays. These scales were selected following the motivation to understand how the response is associated with tsunami, and how the energy evolves until it is completely dissipated. Through signal processing methods, such as discrete and wavelets analysis, we analyze time series of recent tsunamigenic events in the main Chilean coastal cities. Based on this analysis, we propose a conceptual model based on the influence of geomorphological variables on the evolution and decay of tsunami energy. This model acts as a filter from the seismic source to the observed response in coastal zones. Finally, we hope to conclude with practical tools that will establish patterns of behavior and scaling of energy evolution through interconnections from seismic source variables and the geomorphological component to understand the response and predict behavior for a given site.

An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified Representation of Subgrid-Scale Turbulence and Convection

NASA Astrophysics Data System (ADS)

Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Schneider, Tapio; Teixeira, João.

2018-03-01

Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection—such as that they adjust instantaneously to changes in resolved-scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass-flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

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

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE PAGES

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...

2017-03-24

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

The impact of sampling, PCR, and sequencing replication on discerning changes in drinking water bacterial community over diurnal time-scales.

PubMed

Bautista-de Los Santos, Quyen Melina; Schroeder, Joanna L; Blakemore, Oliver; Moses, Jonathan; Haffey, Mark; Sloan, William; Pinto, Ameet J

2016-03-01

High-throughput and deep DNA sequencing, particularly amplicon sequencing, is being increasingly utilized to reveal spatial and temporal dynamics of bacterial communities in drinking water systems. Whilst the sampling and methodological biases associated with PCR and sequencing have been studied in other environments, they have not been quantified for drinking water. These biases are likely to have the greatest effect on the ability to characterize subtle spatio-temporal patterns influenced by process/environmental conditions. In such cases, intra-sample variability may swamp any underlying small, systematic variation. To evaluate this, we undertook a study with replication at multiple levels including sampling sites, sample collection, PCR amplification, and high throughput sequencing of 16S rRNA amplicons. The variability inherent to the PCR amplification and sequencing steps is significant enough to mask differences between bacterial communities from replicate samples. This was largely driven by greater variability in detection of rare bacteria (relative abundance <0.01%) across PCR/sequencing replicates as compared to replicate samples. Despite this, we captured significant changes in bacterial community over diurnal time-scales and find that the extent and pattern of diurnal changes is specific to each sampling location. Further, we find diurnal changes in bacterial community arise due to differences in the presence/absence of the low abundance bacteria and changes in the relative abundance of dominant bacteria. Finally, we show that bacterial community composition is significantly different across sampling sites for time-periods during which there are typically rapid changes in water use. This suggests hydraulic changes (driven by changes in water demand) contribute to shaping the bacterial community in bulk drinking water over diurnal time-scales. Copyright © 2015 Elsevier Ltd. All rights reserved.