scholarly journals Extended Cave Drip Water Time Series Captures the 2015–2016 El Niño in Northern Borneo

2020 ◽  
Vol 47 (5) ◽  
Author(s):  
Shelby A. Ellis ◽  
Kim M. Cobb ◽  
Jessica W. Moerman ◽  
Judson W. Partin ◽  
A. Landry Bennett ◽  
...  
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Drip Water ◽  
Cave Drip Water

scholarly journals ENSO–cave drip water hydrochemical relationship: a 7-year dataset from south-eastern Australia

2016 ◽  
Vol 20 (11) ◽  
pp. 4625-4640 ◽  
Author(s):  
Carol V. Tadros ◽  
Pauline C. Treble ◽  
Andy Baker ◽  
Ian Fairchild ◽  
Stuart Hankin ◽  
...  
Keyword(s):  
Trace Element ◽  
El Niño ◽  
El Nino ◽  
Flow Path ◽  
Geochemical Composition ◽  
Drip Water ◽  
South Eastern ◽  
Cave Drip Water ◽  
Eastern Australia ◽  
Water Signal

Abstract. Speleothems (cave deposits), used for palaeoenvironmental reconstructions, are deposited from cave drip water. Differentiating climate and karst processes within a drip-water signal is fundamental for the correct identification of palaeoenvironmental proxies and ultimately their interpretation within speleothem records. We investigate the potential use of trace element and stable oxygen-isotope (δ18O) variations in cave drip water as palaeorainfall proxies in an Australian alpine karst site. This paper presents the first extensive hydrochemical and δ18O dataset from Harrie Wood Cave, in the Snowy Mountains, south-eastern (SE) Australia. Using a 7-year long rainfall δ18O and drip-water Ca, Cl, Mg / Ca, Sr / Ca and δ18O datasets from three drip sites, we determined that the processes of mixing, dilution, flow path change, carbonate mineral dissolution and prior calcite precipitation (PCP) accounted for the observed variations in the drip-water geochemical composition. We identify that the three monitored drip sites are fed by fracture flow from a well-mixed epikarst storage reservoir, supplied by variable concentrations of dissolved ions from soil and bedrock dissolution. We constrained the influence of multiple processes and controls on drip-water composition in a region dominated by El Niño–Southern Oscillation (ENSO). During the El Niño and dry periods, enhanced PCP, a flow path change and dissolution due to increased soil CO2 production occurred in response to warmer than average temperatures in contrast to the La Niña phase, where dilution dominated and reduced PCP were observed. We present a conceptual model, illustrating the key processes impacting the drip-water chemistry. We identified a robust relationship between ENSO and drip-water trace element concentrations and propose that variations in speleothem Mg / Ca and Sr / Ca ratios may be interpreted to reflect palaeorainfall conditions. These findings inform palaeorainfall reconstruction from speleothems regionally and provide a basis for palaeoclimate studies globally, in regions where there is intermittent recharge variability.

scholarly journals Detection of Mesoscale Seasonal and Interannual Variation in the Vegetation of the Amazon Basin

2005 ◽  
Vol 9 (25) ◽  
pp. 1-16
Author(s):  
Miles G. Logsdon ◽  
Robin Weeks ◽  
Milton Smith ◽  
Jeffery E. Richey ◽  
Victoria Ballester ◽  
...  
Keyword(s):  
Time Series ◽  
El Niño ◽  
Amazon Basin ◽  
El Nino ◽  
Southern Oscillation ◽  
Mathematical Framework ◽  
Spectral Change ◽  
Range Analysis ◽  
Local Variance ◽  
Wide Range

Abstract In the Amazon basin, seasonal and interannual spectral changes measured by satellites result from anthropogenic disturbance and from the interaction between climate variation and the surface cover. Measurements of spectral change, and the characterization of that change, provide information concerning the physical processes evident at this mesoscale. A 17-yr sequence of daily Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) images were analyzed to produce a monthly record of surface spectral change encompassing El Niño–Southern Oscillation (ENSO) cycles. Monthly cloud-free composite images from daily AVHRR data were produced by linear filters that minimized the finescale spatial variance and allowed for a wide range analysis within a consistent mathematical framework. Here the use of a minimized local variance (MLV) filter that produced spatially smooth images in which major land-cover boundaries and spatial gradients are clearly represented is discussed. Changes in the configuration of these boundaries and the composition of the landscape elements they defined are described in terms of quantitative changes in landscape pattern. The time series produced with the MLV filter revealed a marked seasonal difference in the pattern of the landscape and structural differences over the length of the time series. Strikingly, the response of the region to drier El Niño years appears to be delayed in the MLV series, the maximum response being in the year following El Niño with little or no change seen during El Niño.

scholarly journals Analysis and quantification of ENSO-linked changes in the tropical Atlantic cloud vertical distribution using 14 years of MODIS observations

2019 ◽  
Vol 19 (21) ◽  
pp. 13535-13546
Author(s):  
Nils Madenach ◽  
Cintia Carbajal Henken ◽  
René Preusker ◽  
Odran Sourdeval ◽  
Jürgen Fischer
Keyword(s):  
Time Series ◽  
Vertical Distribution ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Tropical Atlantic ◽  
High Cloud

Abstract. A total of 14 years (September 2002 to September 2016) of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) monthly mean cloud data are used to quantify possible changes in the cloud vertical distribution over the tropical Atlantic. For the analysis multiple linear regression techniques are used. For the investigated time period significant linear changes were found in the domain-averaged cloud-top height (CTH) (−178 m per decade), the high-cloud fraction (HCF) (−0.0006 per decade), and the low-cloud amount (0.001 per decade). The interannual variability of the time series (especially CTH and HCF) is highly influenced by the El Niño–Southern Oscillation (ENSO). Separating the time series into two phases, we quantified the linear change associated with the transition from more La Niña-like conditions to a phase with El Niño conditions (Phase 2) and vice versa (Phase 1). The transition from negative to positive ENSO conditions was related to a decrease in total cloud fraction (TCF) (−0.018 per decade; not significant) due to a reduction in the high-cloud amount (−0.024 per decade; significant). Observed anomalies in the mean CTH were found to be mainly caused by changes in HCF rather than by anomalies in the height of cloud tops themselves. Using the large-scale vertical motion ω at 500 hPa (from ERA-Interim ECMWF reanalysis data), the observed anomalies were linked to ENSO-induced changes in the atmospheric large-scale dynamics. The most significant and largest changes were found in regions with strong large-scale upward movements near the Equator. Despite the fact that with passive imagers such as MODIS it is not possible to vertically resolve clouds, this study shows the great potential for large-scale analysis of possible changes in the cloud vertical distribution due to the changing climate by using vertically resolved cloud cover and linking those changes to large-scale dynamics using other observations or model data.

A nonlinear time series model of El Niño

2001 ◽  
Vol 16 (2) ◽  
pp. 139-146 ◽  
Author(s):  
A.D. Hall ◽  
J. Skalin ◽  
T. Teräsvirta
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Nonlinear Time Series ◽  
Time Series Model

Analyzing Fish Condition Factor Index Through Skew-Gaussian Information Theory Quantifiers

2016 ◽  
Vol 15 (02) ◽  
pp. 1650013 ◽  
Author(s):  
Javier E. Contreras-Reyes
Keyword(s):  
Time Series ◽  
El Niño ◽  
Shape Parameter ◽  
Condition Factor ◽  
El Nino ◽  
The Body ◽  
Northern Coast ◽  
Threshold Autoregressive ◽  
El Niño Event ◽  
Engraulis Ringens

Biological-fishery indicators have been widely studied. As such the condition factor (CF) index, which interprets the fatness level of a certain species based on length and weight, has been investigated, too. However, CF has been studied without considering its temporal features and distribution. In this paper, we analyze the CF time series via skew-gaussian distributions that consider the asymmetry produced by extreme events. This index is characterized by a threshold autoregressive model and corresponds to a stationary process depending on the shape parameter of the skew-gaussian distribution. Then we use the Jensen–Shannon (JS) distance to compare CF by length classes. This distance has mathematical advantages over other divergences such as Kullback–Leibler and Jeffrey’s, and the triangular inequality property. Our results are applied to a biological catalogue of anchovy (Engraulis ringens) from the northern coast of Chile, for the period 1990–2010 that consider monthly CF time series by length classes and sex. We find that for high values of shape parameter, JS distance tends to be more sensible to detect discrepancies than Jeffrey’s divergence. In addition, the body condition of male anchovies with higher lengths coincides with the ending of the moderate-strong El Niño event 91–92 and for both males and females, the smaller lengths coincide with the beginning of the strong El Niño event 97–98.

scholarly journals A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship

2020 ◽  
Vol 24 (11) ◽  
pp. 5473-5489 ◽  
Author(s):  
Justin Schulte ◽  
Frederick Policielli ◽  
Benjamin Zaitchik
Keyword(s):  
Time Series ◽  
Time Domain ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Wavelet Coherence ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Time Domain ◽  
Time Domain Correlation

Abstract. Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series changes in time. We show that, even for stationary coherence, the time-domain correlation between two time series weakens if at least one of the time series has changing skewness. To overcome this drawback, a nonlinear coherence method is proposed to quantify the cross-correlation between nonlinear modes embedded in the time series. It is shown that nonlinear coherence and auto-bicoherence spectra can provide additional insight into changing time-domain correlations. The new method is applied to the El Niño–Southern Oscillation (ENSO) and all-India rainfall (AIR), which is intricately linked to hydrological processes across the Indian subcontinent. The nonlinear coherence analysis showed that the skewness of AIR is weakly correlated with that of two ENSO time series after the 1970s, indicating that increases in ENSO skewness after the 1970s at least partially contributed to the weakening ENSO–AIR relationship in recent decades. The implication of this result is that the intensity of skewed El Niño events is likely to overestimate India's drought severity, which was the case in the 1997 monsoon season, a time point when the nonlinear wavelet coherence between AIR and ENSO reached its lowest value in the 1871–2016 period. We determined that the association between the weakening ENSO–AIR relationship and ENSO nonlinearity could reflect the contribution of different nonlinear ENSO modes to ENSO diversity.

scholarly journals Empirical Hydrologic Predictions for Southwestern Poland and Their Relation to Enso Teleconnections

2010 ◽  
Vol 45 (1) ◽  
pp. 11-26 ◽  
Author(s):  
Tomasz Niedzielski
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Early Spring ◽  
Time Interval ◽  
Positive Temperature ◽  
Peak Flows ◽  
Hydrologic Time Series ◽  
Enso Teleconnections ◽  
Sw Poland

Empirical Hydrologic Predictions for Southwestern Poland and Their Relation to Enso TeleconnectionsRecent investigations confirm meaningful but weak teleconnections between the El Niño/Southern Oscillation (ENSO) and hydrology in some European regions. In particular, this finding holds for Polish riverflows in winter and early spring as inferred from integrating numerous geodetic, geophysical and hydrologic time series. The purpose of this study is to examine whether such remote teleconnections may have an influence on hydrologic forecasting. The daily discharge time series from southwestern (SW) Poland spanning the time interval from 1971 to 2006 are examined. A few winter and spring peak flows are considered and the issue of their predictability using empirical forecasting is addressed. Following satisfactory prediction performance reported elsewhere, the multivariate autoregressive method is used and its modification based on the finite impulse response filtering is proposed. The initial phases of peak flows are rather acceptably forecasted but the accuracy of predictions in the vicinity of local maxima of the hydrographs is poorer. It has been hypothesized that ENSO signal slightly influences the predictability of winter and early spring floods in SW Poland. The predictions of flood wave maxima are the most accurate for floods preceded by normal states, less accurate for peak flows after La Niño episodes and highly inaccurate for peak flows preceded by El Niño events. Such a finding can be interpreted in terms of intermittency. Before peak flows preceded by El Niño there are temporarily persistent low flows followed by a consecutive melting leading to a considerable intermittency and hence to difficulties in forecasting. Before peak flows preceded by La Niño episodes there exist ENSO-related positive temperature and precipitation anomalies in SW Poland causing lower, but still considerable, intermittency and thus better, but not entirely correct, predictability of hydrologic time series.

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