Regional climatic drivers of synchronous zooplankton dynamics in north-temperate lakes

2008 ◽  
Vol 65 (5) ◽  
pp. 878-889 ◽  
Author(s):  
James A Rusak ◽  
Norman D Yan ◽  
Keith M Somers
Keyword(s):  
Temporal Dynamics ◽  
Southern Oscillation ◽  
Secchi Depth ◽  
Ice Cover ◽  
Temperate Lakes ◽  
Spring Temperature ◽  
Enso Events ◽  
Temperature And Precipitation ◽  
Zooplankton Dynamics ◽  
North Temperate Lakes

The role that climate plays in determining the temporal dynamics of freshwater zooplankton is poorly understood, despite its potential to synchronize population dynamics on a regional basis. We quantify the spatial synchrony of common zooplankton taxa among lakes in the Dorset, Ontario, area and investigate the climatic mechanisms responsible for these patterns at both annual and seasonal scales. We show that the dynamics of several taxa are characterized by similar patterns of abundance among lakes across the region, suggesting a synchronising effect of climate on zooplankton population abundances. Using multiple regression analyses to compare zooplankton dynamics with climatic and in-lake variables, we find that El Niño – Southern Oscillation (ENSO) events and ice cover variability are among the most important predictors of synchrony at annual and seasonal scales, particularly for Leptodiaptomus and Bosmina. Leptodiaptomus, a dominant herbivore in these lakes, had decreased abundances in years with earlier ice-off dates and shorter periods of ice cover. Secchi depth was also synchronous and appeared to respond to regional meteorological factors (spring temperature and precipitation, ice duration). A warming climate with the ability to modify ice and ENSO dynamics, as well as temperature and precipitation patterns, may also alter the structure and dynamics of zooplankton communities in north-temperate lakes.

Underwater Spectral Attenuation and Its Effect on the Maximum Depth of Angiosperm Colonization

1988 ◽  
Vol 45 (6) ◽  
pp. 1010-1017 ◽  
Author(s):  
P. A. Chambers ◽  
E. E. Prepas
Keyword(s):  
Light Quality ◽  
Secchi Depth ◽  
Maximum Depth ◽  
Regression Equations ◽  
Light Spectrum ◽  
Temperate Lakes ◽  
Underwater Light ◽  
Spectral Attenuation ◽  
Light Quantity ◽  
North Temperate Lakes

Data collected from 23 Alberta lakes and literature values for 45 other north temperate lakes were used to develop regression models to evaluate the effect of underwater light quality on the maximum depth of angiosperm colonization. Unlike most north temperate lakes, eutrophic Alberta lakes have unusually low levels of dissolved colour and, as a result, transmit blue light particularly well. Comparison of regression equations relating the maximum depth of angiosperm colonization (zc) and Secchi depth (D) for lakes with low colour [Formula: see text] and with high colour [Formula: see text] showed that for any Secchi depth, aquatic angiosperms colonized to greater depths in lakes with low colour. These results demonstrate that light quality as well as light quantity determine the maximum depth of angiosperm colonization in lakes. Regional differences in the relation between zc and Secchi depth may therefore be due to variations in the underwater light spectrum.

scholarly journals Spatial-Temporal Distribution of the Freeze–Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020

2021 ◽  
Vol 13 (9) ◽  
pp. 1695
Author(s):  
Weixiao Han ◽  
Chunlin Huang ◽  
Juan Gu ◽  
Jinliang Hou ◽  
Ying Zhang
Keyword(s):  
Machine Learning ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Temporal Distribution ◽  
Ice Cover ◽  
Qinghai Lake ◽  
Gap Filling ◽  
Thaw Cycle ◽  
Break Up ◽  
Ice Phenology

The lake ice phenology variations are vital for the land–surface–water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water–ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.

Climate Index Weighting Schemes for NWS ESP-Based Seasonal Volume Forecasts

2004 ◽  
Vol 5 (6) ◽  
pp. 1076-1090 ◽  
Author(s):  
Kevin Werner ◽  
David Brandon ◽  
Martyn Clark ◽  
Subhrendu Gangopadhyay
Keyword(s):  
Nearest Neighbor ◽  
Southern Oscillation ◽  
Climate Index ◽  
Climate Information ◽  
Streamflow Prediction ◽  
Forecast System ◽  
Ensemble Forecasts ◽  
Weighting Schemes ◽  
Temperature And Precipitation ◽  
Spring Runoff

Abstract This study compares methods to incorporate climate information into the National Weather Service River Forecast System (NWSRFS). Three small-to-medium river subbasins following roughly along a longitude in the Colorado River basin with different El Niño–Southern Oscillation signals were chosen as test basins. Historical ensemble forecasts of the spring runoff for each basin were generated using modeled hydrologic states and historical precipitation and temperature observations using the Ensemble Streamflow Prediction (ESP) component of the NWSRFS. Two general methods for using a climate index (e.g., Niño-3.4) are presented. The first method, post-ESP, uses the climate index to weight ensemble members from ESP. Four different post-ESP weighting schemes are presented. The second method, preadjustment, uses the climate index to modify the temperature and precipitation ensembles used in ESP. Two preadjustment methods are presented. This study shows the distance-sensitive nearest-neighbor post-ESP to be superior to the other post-ESP weighting schemes. Further, for the basins studied, forecasts based on post-ESP techniques outperformed those based on preadjustment techniques.

scholarly journals The Response of Tropical Atmospheric Energy Budgets to ENSO*

2013 ◽  
Vol 26 (13) ◽  
pp. 4710-4724 ◽  
Author(s):  
Michael Mayer ◽  
Kevin E. Trenberth ◽  
Leopold Haimberger ◽  
John T. Fasullo
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Warm Pool ◽  
Smooth Transition ◽  
Energy Budgets ◽  
Enso Events ◽  
El Niño Modoki ◽  
Static Energy ◽  
The Tropics

Abstract The variability of zonally resolved tropical energy budgets in association with El Niño–Southern Oscillation (ENSO) is investigated. The most recent global atmospheric reanalyses from 1979 to 2011 are employed with removal of apparent discontinuities to obtain best possible temporal homogeneity. The growing length of record allows a more robust analysis of characteristic patterns of variability with cross-correlation, composite, and EOF methods. A quadrupole anomaly pattern is found in the vertically integrated energy divergence associated with ENSO, with centers over the Indian Ocean, the Indo-Pacific warm pool, the eastern equatorial Pacific, and the Atlantic. The smooth transition, particularly of the main maxima of latent and dry static energy divergence, from the western to the eastern Pacific is found to require at least two EOFs to be adequately described. The canonical El Niño pattern (EOF-1) and a transition pattern (EOF-2; referred to as El Niño Modoki by some authors) form remarkably coherent ENSO-related anomaly structures of the tropical energy budget not only over the Pacific but throughout the tropics. As latent and dry static energy divergences show strong mutual cancellation, variability of total energy divergence is smaller and more tightly coupled to local sea surface temperature (SST) anomalies and is mainly related to the ocean heat discharge and recharge during ENSO peak phases. The complexity of the structures throughout the tropics and their evolution during ENSO events along with their interactions with the annual cycle have often not been adequately accounted for; in particular, the El Niño Modoki mode is but part of the overall evolutionary patterns.

The relationship between the El Niño Southern Oscillation and Australian monsoon rainfall on decadal time-scales

2021 ◽  
Author(s):  
Hanna Heidemann ◽  
Joachim Ribbe ◽  
Benjamin J. Henley ◽  
Tim Cowan ◽  
Christa Pudmenzky ◽  
...  
Keyword(s):  
Monsoon Rainfall ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Eastern Pacific ◽  
Central Pacific ◽  
Australian Monsoon ◽  
Enso Events ◽  
Pacific Decadal Variability ◽  
Prediction Systems ◽  
Different Response

<p>This research analyses the observed relationship between eastern and central Pacific El Niño Southern Oscillation (ENSO) events and Australian monsoon rainfall (AUMR) on a decadal timescale during the December to March monsoon months. To assess the decadal influence of the different flavours of ENSO on the AUMR, we focus on the phases of the Interdecadal Pacific Oscillation (IPO) over the period 1920 to 2020.  The AUMR is characterized by substantial decadal variability, which appears to be linked to the positive and negative phases of the IPO. During the past two historical negative IPO phases, significant correlations have been observed between central Pacific sea surface temperature (SST) anomalies and AUMR over both the northeast and northwest of Australia. This central Pacific SST-AUMR relationship has strengthened from the first negative IPO phase (mid-1940s to the mid-1970s) to the second (late 1990s to mid-2010s), while the eastern Pacific SST-AUMR influence has weakened. Composite rainfall anomalies over Australia reveal a different response of AUMR to central Pacific El Niño/La Niña and eastern Pacific La Niña events during positive IPO and negative IPO phases. This research clearly shows that ENSO's influence on AUMR is modulated by Pacific decadal variability, however this teleconnection, in itself, can change between similar decadal Pacific states.  Going forward, as decadal prediction systems improve and become more mainstream, the IPO phase could be used as a potential source for decadal predictability of the tendency of AUMR.  </p>

Impact of strong El Niño events on river discharge in South America

2021 ◽  
Author(s):  
Markus Deppner ◽  
Bedartha Goswami
Keyword(s):  
Machine Learning ◽  
Missing Data ◽  
South America ◽  
River Discharge ◽  
Amazon Basin ◽  
Missing Values ◽  
Southern Oscillation ◽  
Enso Events ◽  
Streamflow Data ◽  
The Impact

<p>The impact of the El Niño Southern Oscillation (ENSO) on rivers are well known, but most existing studies involving streamflow data are severely limited by data coverage. Time series of gauging stations fade in and out over time, which makes hydrological large scale and long time analysis or studies of rarely occurring extreme events challenging. Here, we use a machine learning approach to infer missing streamflow data based on temporal correlations of stations with missing values to others with data. By using 346 stations, from the “Global Streamflow Indices and Metadata archive” (GSIM), that initially cover the 40 year timespan in conjunction with Gaussian processes we were able to extend our data by estimating missing data for an additional 646 stations, allowing us to include a total of 992 stations. We then investigate the impact of the 6 strongest El Niño (EN) events on rivers in South America between 1960 and 2000. Our analysis shows a strong correlation between ENSO events and extreme river dynamics in the southeast of Brazil, Carribean South America and parts of the Amazon basin. Furthermore we see a peak in the number of stations showing maximum river discharge all over Brazil during the EN of 1982/83 which has been linked to severe floods in the east of Brazil, parts of Uruguay and Paraguay. However EN events in other years with similar intensity did not evoke floods with such magnitude and therefore the additional drivers of the 1982/83  floods need further investigation. By using machine learning methods to infer data for gauging stations with missing data we were able to extend our data by almost three-fold, revealing a possible heavier and spatially larger impact of the 1982/83 EN on South America's hydrology than indicated in literature.</p>

scholarly journals Late Holocene environmental reconstructions and their implications on flood events, typhoon, and agricultural activities in NE Taiwan

2014 ◽  
Vol 10 (5) ◽  
pp. 1857-1869 ◽  
Author(s):  
L.-C. Wang ◽  
H. Behling ◽  
T.-Q. Lee ◽  
H.-C. Li ◽  
C.-A. Huh ◽  
...  
Keyword(s):  
Little Ice Age ◽  
Southern Oscillation ◽  
Phase 1 ◽  
Warm Pool ◽  
Ice Age ◽  
Agricultural Activities ◽  
Flood Events ◽  
Climate Conditions ◽  
Hydrological Conditions ◽  
Enso Events

Abstract. We reconstructed paleoenvironmental changes from a sediment archive of a lake in the floodplain of the Ilan Plain of NE Taiwan on multi-decadal resolution for the last ca. 1900 years. On the basis of pollen and diatom records, we evaluated past floods, typhoons, and agricultural activities in this area which are sensitive to the hydrological conditions in the western Pacific. Considering the high sedimentation rates with low microfossil preservations in our sedimentary record, multiple flood events were. identified during the period AD 100–1400. During the Little Ice Age phase 1 (LIA 1 – AD 1400–1620), the abundant occurrences of wetland plant (Cyperaceae) and diatom frustules imply less flood events under stable climate conditions in this period. Between AD 500 and 700 and the Little Ice Age phase 2 (LIA 2 – AD 1630–1850), the frequent typhoons were inferred by coarse sediments and planktonic diatoms, which represented more dynamical climate conditions than in the LIA 1. By comparing our results with the reconstructed changes in tropical hydrological conditions, we suggested that the local hydrology in NE Taiwan is strongly influenced by typhoon-triggered heavy rainfalls, which could be influenced by the variation of global temperature, the expansion of the Pacific warm pool, and the intensification of El Niño–Southern Oscillation (ENSO) events.

scholarly journals Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review

2018 ◽  
Vol 147 ◽  
Author(s):  
A. Aswi ◽  
S. M. Cramb ◽  
P. Moraga ◽  
K. Mengersen
Keyword(s):  
Dengue Fever ◽  
Random Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Assessment Tool ◽  
Temporal Dynamics ◽  
Random Effect ◽  
Temperature And Precipitation ◽  
Generalised Linear Mixed Model ◽  
Spatio Temporal

AbstractDengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.

scholarly journals The Influence of Sea Surface Temperatures on the Northern Winter Stratosphere: Ensemble Simulations with the MAECHAM5 Model

2006 ◽  
Vol 19 (16) ◽  
pp. 3863-3881 ◽  
Author(s):  
E. Manzini ◽  
M. A. Giorgetta ◽  
M. Esch ◽  
L. Kornblueh ◽  
E. Roeckner
Keyword(s):  
Lower Stratosphere ◽  
Southern Oscillation ◽  
Internal Variability ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Mean Flow ◽  
Enso Events ◽  
Surface Temperatures ◽  
Northern Winter ◽  
Mean State

Abstract The role of interannual variations in sea surface temperatures (SSTs) on the Northern Hemisphere winter polar stratospheric circulation is addressed by means of an ensemble of nine simulations performed with the middle atmosphere configuration of the ECHAM5 model forced with observed SSTs during the 20-yr period from 1980 to 1999. Results are compared to the 40-yr ECMWF Re-Analysis (ERA-40). Three aspects have been considered: the influence of the interannual SST variations on the climatological mean state, the response to El Niño–Southern Oscillation (ENSO) events, and the influence on systematic temperature changes. The strongest influence of SST variations has been found for the warm ENSO events considered. Namely, it has been found that the large-scale pattern associated with the extratropical tropospheric response to the ENSO phenomenon during northern winter enhances the forcing and the vertical propagation into the stratosphere of the quasi-stationary planetary waves emerging from the troposphere. This enhanced planetary wave disturbance thereafter results in a polar warming of a few degrees in the lower stratosphere in late winter and early spring. Consequently, the polar vortex is weakened, and the warm ENSO influence clearly emerges also in the zonal-mean flow. In contrast, the cold ENSO events considered do not appear to have an influence distinguishable from that of internal variability. It is also not straightforward to deduce the influence of the SSTs on the climatological mean state from the simulations performed, because the simulated internal variability of the stratosphere is large, a realistic feature. Moreover, the results of the ensemble of simulations provide weak to negligible evidence for the possibility that SST variations during the two decades considered are substantially contributing to changes in the polar temperature in the winter lower stratosphere.

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