The Use of Eigenvectors for Climatic Estimates

Stidd, Charles K.

doi:10.1175/1520-0450(1967)006<0255:tuoefc>2.0.co;2

Cited by 79 publications

(39 citation statements)

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“…Stidd, 1967;Bartlein, 1982;Gottschalk, 1985;Hisdal & Tveito, 1993;Krasovskaia & Gottschalk, 1995;Famiglietti et al, 1995;Krasovskaia et al, 1999;Sauquet et al, 2000).…”

Section: Dimensionality Reduction With Eof and Phase-space Representasupporting

confidence: 71%

River flow regimes in a changing climate

Krasovskaia

Gottschalk

2002

Hydrological Sciences Journal

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A river flow regime describes an average seasonal behaviour of flow and reflects the climatic and physiographic conditions in a basin. Differences in the regularity (stability) of the seasonal patterns reflect different dimensionality of the flow regimes, which can change subject to changes in climate conditions. The empirical orthogonal functions (EOF) approach can be used to describe the intrinsic dimension of river flow regimes and is also an adopted method for reducing the phase space in connection to climate change studies, especially in studies of nonlinear dynamic systems with preferred states. A large data set of monthly river flow for the Nordic countries has been investigated in the phase space reduced to the first few amplitude functions to trace a possible signature of climate change on the seasonal flow patterns. The probability density functions (PDF) of the weight coefficients and their possible change over time were used as an indicator of climate change. Two preferred states were identified connected to stable snowmelt-fed and rainfed flow regimes. The results indicate changes in the PDF patterns with time towards higher frequencies of rainfed regime types. The dynamics of seasonal patterns studied in terms of PDF renders it an adequate and convenient characterization, helping to avoid bias connected to flow regime classifications as well as uncertainties inferred by a modelling approach.Key words river flow regime; climate change; attractor Régimes hydrologiques et évolution du climat Résumé Le régime hydrologique d'un cours d'eau décrit l'évolution saisonnière moyenne de son écoulement et reflète les conditions climatiques et physiographiques de son bassin versant. La variabilité interannuelle de cette évolution de l'écoulement reflète une dimension propre à chaque régime, liée à sa régularité (stabilité), et qui peut aussi évoluer en fonction de changements climatiques. Les fonctions orthogonales empiriques (FOE), qui peuvent être utilisées pour évaluer la dimension intrinsèque des régimes hydrologiques, sont également adaptées pour réduire l'espace des phases en relation avec des études sur le changement climatique, en particulier dans l'étude de systèmes chaotiques non-linéaires présentant des états préférentiels. Un vaste jeu de données de débit mensuel, couvrant les pays nordiques, a ainsi été examiné dans l'espace des phases correspondant aux premières fonctions d'amplitude afin d'y rechercher la trace d'un éventuel changement climatique dans les variations saisonnières d'écoulement. Les fonctions de densité de probabilité (FDP) des coefficients de pondération et leur évolution possible au fil du temps ont été considérées comme un indicateur de changement climatique. Deux états préférentiels ont été identifiés, correspondant l'un à un régime nival stable, l'autre à un régime pluvial. Les résultats montrent une évolution des FDP au cours du temps allant vers une plus grande proportion de régimes pluviaux. La dynamique des schémas saisonniers, étudiée à travers ces FDP, devient un...

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“…Stidd, 1967;Bartlein, 1982;Gottschalk, 1985;Hisdal & Tveito, 1993;Krasovskaia & Gottschalk, 1995;Famiglietti et al, 1995;Krasovskaia et al, 1999;Sauquet et al, 2000).…”

Section: Dimensionality Reduction With Eof and Phase-space Representasupporting

confidence: 71%

River flow regimes in a changing climate

Krasovskaia

Gottschalk

2002

Hydrological Sciences Journal

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“…The technique of applying PCA to mean monthly rainfall climatologies has long been noted as an efficient summary of the salient features of the annual cycle of precipitation (Stidd, 1967;Comrie and Glenn, 1998;Jayawardene et al, 2005). Data included in this analysis were chosen from a total of 28 Caribbean weather stations in the Global Historical Climate Network Version 2 (as available from the NOAA National Climate Data Centre (NCDC) website) ( Table I).…”

Section: Methodsmentioning

confidence: 99%

Spatial variability of the Caribbean mid-summer drought and relation to north Atlantic high circulation

2008

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Annual rainfall in the Caribbean exhibits a bimodal structure with two rainfall maxima (May-June and September-October) separated by what has been termed a mid-summer drought (MSD) (July-August). Despite general acceptance of the intensification and expansion of the North Atlantic High Pressure (NAHP) as the cause of the Caribbean MSD, it has been noted in several studies that the influence of the NAHP may not be consistent across the region. The purpose of this research is to better understand the Caribbean MSD by mapping the spatial co-variability of the Caribbean MSD and then determining the association between these spatial patterns and NAHP circulation. The spatial variability of the Caribbean MSD is identified through mapping of Principal Component Analysis (PCA) loadings of Caribbean MSD season rainfall time series. A correlation analysis was completed between monthly MSD region rainfall time series and measures of the NAHP to assess the degree of association between the spatial variability in the Caribbean MSD and NAHP circulation. The PCA identified six MSD regions, the northwestern Caribbean, the interior Caribbean, the eastern rim Caribbean, Coro Venezuela, Grantley Barbados, and a transition zone. The spatial pattern of the MSD regions suggests that the NAHP impacts the eastern Caribbean first and then progresses westward as the summer develops. In regard to the association between NAHP circulation and MSD region precipitation time series, correlation analysis indicates that overall, a modified Bermuda High Index (BHI) is a more effective tool in evaluating the association between the NAHP and Caribbean MSD as compared to the traditional indices, NAO EOF and BHI. Lagged correlations support previous findings that the winter preceding a particularly dry summer in the Caribbean is characterized by a strong pressure gradient on the southeastern flank of the NAHP; implying stronger Trade Winds, cooler sea surface temperatures, and reduced convective rainfall.

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“…The SVD technique is a well established method for diagonalizing non-square matrices similarly to related techniques such as "principal components" or "empirical orthogonal functions" analysis (Bretherton et al 1992;Stidd 1967). Each time series is arranged as a matrix with each column including all data points for one month and successive columns including data for separate months, The data are normalized by subtracting the yearly mean for each grid point and by subtracting the monthly mean from each of the monthly fields.…”

Section: 3mentioning

confidence: 99%

Satellite remote sensing of global rainfall using passive microwave radiometry

Ferriday¹

1994

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The Use of Eigenvectors for Climatic Estimates

Cited by 79 publications

References 0 publications

River flow regimes in a changing climate

River flow regimes in a changing climate

Spatial variability of the Caribbean mid-summer drought and relation to north Atlantic high circulation

Satellite remote sensing of global rainfall using passive microwave radiometry

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