scholarly journals Pacific Decadal Oscillation Climate Variability and Temporal Pattern of Winter Flows in Northwestern North America

2010 ◽  
Vol 11 (4) ◽  
pp. 917-933 ◽  
Author(s):  
M. N. Khaliq ◽  
P. Gachon
Keyword(s):  
Time Series ◽  
Water Resources ◽  
North America ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
Large Scale ◽  
Temporal Variations ◽  
Average Percentage ◽  
Daily Streamflow ◽  
Northwestern North America

Abstract There is growing concern about the effects of large-scale oceanic atmospheric climate variability, such as the Pacific decadal oscillation (PDO), on regional hydrology and water resources. In this paper, the effects of PDO on temporal patterns of winter (January–March) flow in northwestern North America (NWNA), which is believed to be a PDO-sensitive region, is studied for the period 1943–2007 using daily streamflow data from a much larger set of 179 stations, compared to previous studies in which only smaller subsets of these stations were analyzed. Time series of winter flows were divided into two nonoverlapping blocks corresponding to change points detected in time series of December–March mean monthly PDO indices. Both parametric and nonparametric measures of correlation and average percentage differences and average standardized differences from the period-of-record mean were explored. Like some of the previous studies, it is found that, on average, winter flows tend to be higher (lower) during the warm (cold) phase of the PDO and that establishes the physical link between large-scale climate variability and basin response. It is shown that the serial structure of time series of PDO indices conforms to that of a stochastic process with long-term persistence (LTP). Based on this finding and the climate–streamflow physical link, it is plausible to investigate temporal variations in winter flows with the LTP hypothesis, in addition to assuming merely independence (IND) or short-term persistence (STP). The results of the analysis demonstrate that the LTP mechanism, in combination with the STP, is able to explain more than half of the significant trends noted, with the IND assumption suggesting that the significance of trends reported in previous studies in NWNA may have been overstated. This result has important implications for future planning of regional water resources.

scholarly journals Large Scale Solar Magnetic Fields: Temporal Variations

2004 ◽  
Vol 219 ◽  
pp. 552-556 ◽  
Author(s):  
R. Knaack ◽  
J. O. Stenflo
Keyword(s):  
Magnetic Field ◽  
Time Series ◽  
Large Scale ◽  
Solar Magnetic Field ◽  
Temporal Variations ◽  
Solar Photosphere ◽  
Solar Cycles ◽  
Radial Magnetic Field ◽  
Quasi Biennial Oscillation ◽  
Harmonic Decomposition

We have investigated the temporal evolution of the solar magnetic field during solar cycles 20, 21 and 22 by means of spherical harmonic decomposition and subsequent time series analysis. A 33 yr and a 25 yr time series of daily magnetic maps of the solar photosphere, recorded at the Mt. Wilson and NSO/Kitt Peak observatories respectively, were used to calculate the spherical coefficients of the radial magnetic field. Fourier and wavelet analysis were then applied to deduce the temporal variations. We compare the results of the two datasets and present examples of zonal modes which show significant variations, e. g. with a period of approx. 2.0—2.5 years. We provide evidence that this quasi-biennial oscillation originates mainly from the southern hemisphere. Furthermore, we show that low degree modes with odd l — m exhibit periods of 29.2 and 28.1 days while modes with even l — m show a dominant period of 26.9 days. A resonant modal structure of the solar magnetic field (apart from the 22 yr cycle) has not been found.

scholarly journals The Use of Large-Scale Climate Indices in Monthly Reservoir Inflow Forecasting and Its Application on Time Series and Artificial Intelligence Models

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 374 ◽  
Author(s):  
Taereem Kim ◽  
Ju-Young Shin ◽  
Hanbeen Kim ◽  
Sunghun Kim ◽  
Jun-Haeng Heo
Keyword(s):  
Artificial Intelligence ◽  
Time Series ◽  
Climate Variability ◽  
Large Scale ◽  
Climate Indices ◽  
Exogenous Variables ◽  
Inflow Forecasting ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Reservoir Inflow

Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect correlation with hydrologic variables. This study aims to use large-scale climate indices in monthly reservoir inflow forecasting for considering climate variability. For this purpose, time series and artificial intelligence models, such as Seasonal AutoRegressive Integrated Moving Average (SARIMA), SARIMA with eXogenous variables (SARIMAX), Artificial Neural Network (ANN), Adaptive Neural-based Fuzzy Inference System (ANFIS), and Random Forest (RF) models were employed with two types of input variables, autoregressive variables (AR-) and a combination of autoregressive and exogenous variables (ARX-). Several statistical methods, including ensemble empirical mode decomposition (EEMD), were used to select the lagged climate indices. Finally, monthly reservoir inflow was forecasted by SARIMA, SARIMAX, AR-ANN, ARX-ANN, AR-ANFIS, ARX-ANFIS, AR-RF, and ARX-RF models. As a result, the use of climate indices in artificial intelligence models showed a potential to improve the model performance, and the ARX-ANN and AR-RF models generally showed the best performance among the employed models.

scholarly journals The Influence of Large-Scale Climate Variability on Winter Maximum Daily Precipitation over North America

2010 ◽  
Vol 23 (11) ◽  
pp. 2902-2915 ◽  
Author(s):  
Xuebin Zhang ◽  
Jiafeng Wang ◽  
Francis W. Zwiers ◽  
Pavel Ya Groisman
Keyword(s):  
North America ◽  
Climate Variability ◽  
El Niño ◽  
Extreme Precipitation ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
Winter Season ◽  
The North

Abstract The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley.

scholarly journals The Influence of European Climate Variability Mechanism on Air Temperatures in Romania

2014 ◽  
Vol 8 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Nicoleta Ionac ◽  
Monica Matei
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Large Scale ◽  
Empirical Orthogonal Functions ◽  
Spatial And Temporal Variability ◽  
Orthogonal Functions ◽  
Mean Values ◽  
European Climate ◽  
Air Temperatures ◽  
And Shifts

Abstract The present paper investigates on the spatial and temporal variability of maximum and minimum air-temperatures in Romania and their connection to the European climate variability. The European climate variability is expressed by large scale parameters, which are roughly represented by the geopotential height at 500 hPa (H500) and air temperature at 850 hPa (T850). The Romanian data are represented by the time series at 22 weather stations, evenly distributed over the entire country’s territory. The period that was taken into account was 1961-2010, for the summer and winter seasons. The method of empirical orthogonal functions (EOF) has been used, in order to analyze the connection between the temperature variability in Romania and the same variability at a larger scale, by taking into consideration the atmosphere circulation. The time series associated to the first two EOF patterns of local temperatures and large-scale anomalies were considered with regard to trends and shifts in their mean values. The non- Mann-Kendall and Pettitt parametric tests were used in this respect. The results showed a strong correlation between T850 parameter and minimum and maximum air temperatures in Romania. Also, the ample variance expressed by the first EOF configurations suggests a connection between local and large scale climate variability.

scholarly journals Influence of Modes of Climate Variability on Global Temperature Extremes

2008 ◽  
Vol 21 (15) ◽  
pp. 3872-3889 ◽  
Author(s):  
Jesse Kenyon ◽  
Gabriele C. Hegerl
Keyword(s):  
North America ◽  
Climate Variability ◽  
Large Scale ◽  
Southern Oscillation ◽  
Temperature Extremes ◽  
Modes Of Variability ◽  
The North ◽  
The Pacific ◽  
The North Atlantic Oscillation ◽  
Modes Of Climate Variability

Abstract The influence of large-scale modes of climate variability on worldwide summer and winter temperature extremes has been analyzed, namely, that of the El Niño–Southern Oscillation, the North Atlantic Oscillation, and Pacific interdecadal climate variability. Monthly indexes for temperature extremes from worldwide land areas are used describe moderate extremes, such as the number of exceedences of the 90th and 10th climatological percentiles, and more extreme events such as the annual, most extreme temperature. This study examines which extremes show a statistically significant (5%) difference between the positive and negative phases of a circulation regime. Results show that temperature extremes are substantially affected by large-scale circulation patterns, and they show distinct regional patterns of response to modes of climate variability. The effects of the El Niño–Southern Oscillation are seen throughout the world but most clearly around the Pacific Rim and throughout all of North America. Likewise, the influence of Pacific interdecadal variability is strongest in the Northern Hemisphere, especially around the Pacific region and North America, but it extends to the Southern Hemisphere. The North Atlantic Oscillation has a strong continent-wide effect for Eurasia, with a clear but weaker effect over North America. Modes of variability influence the shape of the daily temperature distribution beyond a simple shift, often affecting cold and warm extremes and sometimes daytime and nighttime temperatures differently. Therefore, for reliable attribution of changes in extremes as well as prediction of future changes, changes in modes of variability need to be accounted for.

scholarly journals Assessment of Groundwater Resource in Climate Variability Context at Sinematiali (North of Côte d'Ivoire)

2020 ◽  
Vol 1 (5) ◽  
Author(s):  
Omer Zephir De Lasme ◽  
Avy Stephane Koffi ◽  
Dodo Guy Gnali Cedric
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Climate Variability ◽  
Water Resources Management ◽  
Integrated Water Resources Management ◽  
Statistical Test ◽  
Groundwater Resource ◽  
Resources Management ◽  
Pettitt Test ◽  
Software Models

Study of climate variability gets great importance for integrated water resources management. This work examines impact of climate variability on the evolution of water resources in the Bandama sub-watershed at Sinematiali with a view of better management. The time series of rainfall and discharge were used as a database for this purpose. Known calculation hydrologic methods of Nicholson, Maillet as well as the statistical test for breaking detection (Pettitt test) were applied. The effective rain and recharge were estimated by using the ESPERE software models over the period 1980 to 1987. Climate variability is characterized by alternative season of wet, normal, and dry periods, and a pluviometry break occurred in 1984 year. The annual effective rain was assessed from 30 to 570 mm while recharge of aquifers estimated between 2 and 333 mm. This work constitutes a fundamental base for modeling water resources management at Sinematiali.

scholarly journals North American Winter Dipole: Observed and Simulated Changes in Circulations

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 793 ◽  
Author(s):  
Yu-Tang Chien ◽  
S.-Y. Simon Wang ◽  
Yoshimitsu Chikamoto ◽  
Steve L. Voelker ◽  
Jonathan D. D. Meyer ◽  
...  
Keyword(s):  
North America ◽  
North American ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulations ◽  
The North ◽  
Weather Events ◽  
The Pacific ◽  
Climate Model Simulations ◽  
Northwestern North America

In recent years, a pair of large-scale circulation patterns consisting of an anomalous ridge over northwestern North America and trough over northeastern North America was found to accompany extreme winter weather events such as the 2013–2015 California drought and eastern U.S. cold outbreaks. Referred to as the North American winter dipole (NAWD), previous studies have found both a marked natural variability and a warming-induced amplification trend in the NAWD. In this study, we utilized multiple global reanalysis datasets and existing climate model simulations to examine the variability of the winter planetary wave patterns over North America and to better understand how it is likely to change in the future. We compared between pre- and post-1980 periods to identify changes to the circulation variations based on empirical analysis. It was found that the leading pattern of the winter planetary waves has changed, from the Pacific–North America (PNA) mode to a spatially shifted mode such as NAWD. Further, the potential influence of global warming on NAWD was examined using multiple climate model simulations.

scholarly journals Attribution of spatial and temporal variations in terrestrial methane flux over North America

2010 ◽  
Vol 7 (11) ◽  
pp. 3637-3655 ◽  
Author(s):  
X. F. Xu ◽  
H. Q. Tian ◽  
C. Zhang ◽  
M. L. Liu ◽  
W. Ren ◽  
...  
Keyword(s):  
North America ◽  
Global Change ◽  
Climate Variability ◽  
Spatial Data ◽  
Climatic Variability ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Ch4 Emission ◽  
Ch4 Flux ◽  
Change Factors

Abstract. The attribution of spatial and temporal variations in terrestrial methane (CH4) flux is essential for assessing and mitigating CH4 emission from terrestrial ecosystems. In this study, we used a process-based model, the Dynamic Land Ecosystem Model (DLEM), in conjunction with spatial data of six major environmental factors to attribute the spatial and temporal variations in the terrestrial methane (CH4) flux over North America from 1979 to 2008 to six individual driving factors and their interaction. Over the past three decades, our simulations indicate that global change factors accumulatively contributed 23.51 ± 9.61 T g CH4-C (1 Tg = 1012 g) emission over North America, among which ozone (O3) pollution led to a reduced CH4 emission by 2.30 ± 0.49 T g CH4-C. All other factors including climate variability, nitrogen (N) deposition, elevated atmospheric carbon dioxide (CO2), N fertilizer application, and land conversion enhanced terrestrial CH4 emissions by 19.80 ± 12.42 T g CH4-C, 0.09 ± 0.02 T g CH4-C, 6.80 ± 0.86 T g CH4-C, 0.01 ± 0.001 T g CH4-C, and 3.95 ± 0.38 T g CH4-C, respectively, and interaction between/among these global change factors led to a decline of CH4 emission by 4.84 ± 7.74 T g CH4-C. Climate variability and O3 pollution suppressed, while other factors stimulated CH4 emission over the USA; climate variability significantly enhanced, while all the other factors exerted minor effects, positive or negative, on CH4 emission in Canada; Mexico functioned as a sink for atmospheric CH4 with a major contribution from climate change. Climatic variability dominated the inter-annual variations in terrestrial CH4 flux at both continental and country levels. Precipitation played an important role in the climate-induced changes in terrestrial CH4 flux at both continental and country-levels. The relative importance of each environmental factor in determining the magnitude of CH4 flux showed substantially spatial variation across North America. This factorial attribution of CH4 flux in North America might benefit policy makers who would like to curb climate warming by reducing CH4 emission.

scholarly journals The Importance of Climate Variability to Wind-Driven Modulation of Hypoxia in Chesapeake Bay

2010 ◽  
Vol 40 (6) ◽  
pp. 1435-1440 ◽  
Author(s):  
Malcolm E. Scully
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Chesapeake Bay ◽  
Wind Direction ◽  
Large Scale ◽  
Nitrogen Loading ◽  
Nutrient Inputs ◽  
Westerly Direction ◽  
Hypoxic Volume

Abstract Extensive hypoxia remains a problem in Chesapeake Bay, despite some reductions in estimated nutrient inputs. An analysis of a 58-yr time series of summer hypoxia reveals that a significant fraction of the interannual variability observed in Chesapeake Bay is correlated to changes in summertime wind direction that are the result of large-scale climate variability. Beginning around 1980, the surface pressure associated with the summer Bermuda high has weakened, favoring winds from a more westerly direction, the direction most correlated with observed hypoxia. Regression analysis suggests that the long-term increase in hypoxic volume observed in this dataset is only accounted for when both changes in wind direction and nitrogen loading are considered.

Sign in / Sign up

Export Citation Format

Share Document