scholarly journals El Niño induced changes to the Bolivar Channel ecosystem (Galapagos): comparing model simulations with historical biomass time series

2012 ◽  
Vol 448 ◽  
pp. 7-22 ◽  
Author(s):  
M Wolff ◽  
DJ Ruiz ◽  
M Taylor
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Model Simulations ◽  
Induced Changes

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

scholarly journals 1997/98 El Niño–Induced Changes in Rainfall Vertical Structure in the East Pacific

2011 ◽  
Vol 24 (24) ◽  
pp. 6373-6391 ◽  
Author(s):  
Rui Li ◽  
Qilong Min ◽  
Yunfei Fu
Keyword(s):  
El Niño ◽  
Large Scale ◽  
Vertical Structure ◽  
Rain Rate ◽  
El Nino ◽  
Latent Heating ◽  
East Pacific ◽  
Surface Rain Rate ◽  
Induced Changes ◽  
The Impact

Abstract The 1997/98 El Niño–induced changes in rainfall vertical structure in the east Pacific (EP) are investigated by using collocated Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and associated daily SST and 6-hourly reanalysis data during January, February, March, and April of 1998, 1999, and 2000. This study shows that there are five key parameters, that is, surface rain rate, precipitation-top height (or temperature), and precipitation growth rates at upper, middle, and low layers to define a rainfall profile, and those five key parameters are strongly influenced by both SST and large-scale dynamics. Under the influence of 1997/98 El Niño, the precipitation-top heights in the EP were systematically higher by about 1 km than those under non–El Niño conditions, while the freezing level was about 0.5 km higher. Under the constraints of rain type, surface rain rate, and the precipitation top, the shape of rainfall profile still showed significant differences: the rain growth was relatively faster in the mid-layer (−5° to +2°C isotherm) but slower in the lower layer (below +2°C isotherm) under the influence of El Niño. It is also evident that the dependence of precipitation top height on SST was stronger under large-scale decent (non–El Niño) circulations but much weaker under large-scale ascent (El Niño) circulations. The combined effect of larger vertical extent and greater growth rate in the middle layer further shifted latent heating upward as compared with the impact of horizontal changes in the rain type fractions (convective versus stratiform). Such additional latent heating shift would certainly further elevate circulation centers and strengthen the upper-layer circulation.

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 Oceanic Origins of Historical Southwest Asia Precipitation During the Boreal Cold Season

2017 ◽  
Vol 30 (8) ◽  
pp. 2885-2903 ◽  
Author(s):  
Andrew Hoell ◽  
Mathew Barlow ◽  
Forest Cannon ◽  
Taiyi Xu
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Atmospheric Model ◽  
Cold Season ◽  
Southwest Asia ◽  
Regional Variability ◽  
Model Simulations ◽  
Dry Conditions

While a strong influence on cold season southwest Asia precipitation by Pacific sea surface temperatures (SSTs) has been previously established, the scarcity of southwest Asia precipitation observations prior to 1960 renders the region’s long-term precipitation history largely unknown. Here a large ensemble of atmospheric model simulations forced by observed time-varying boundary conditions for 1901–2012 is used to examine the long-term sensitivity of November–April southwest Asia precipitation to Pacific SSTs. It is first established that the models are able to reproduce the key features of regional variability during the best-observed 1960–2005 period and then the pre-1960 variability is investigated using the model simulations. During the 1960–2005 period, both the mean precipitation and the two leading modes of precipitation variability during November–April are reasonably simulated by the atmospheric models, which include the previously identified relationships with El Niño–Southern Oscillation (ENSO) and the multidecadal warming of Indo-Pacific SSTs. Over the full 1901–2012 period, there are notable variations in precipitation and in the strength of the SST influence. A long-term drying of the region is associated with the Indo-Pacific warming, with a nearly 10% reduction in westernmost southwest Asia precipitation during 1938–2012. The influence of ENSO on southwest Asia precipitation varied in strength throughout the period: strong prior to the 1950s, weak between 1950 and 1980, and strongest after the 1980s. These variations were not antisymmetric between ENSO phases. El Niño was persistently related with anomalously wet conditions throughout 1901–2012, whereas La Niña was not closely linked to precipitation anomalies prior to the 1970s but has been associated with exceptionally dry conditions thereafter.

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.

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