%0 Journal Article %1 Whitcher.Guttorp.ea2000 %A Whitcher, B. %A Guttorp, P. %A Percival, D. B. %D 2000 %I Amer Geophysical Union %J Journal of Geophysical Research-atmospheres %K 40-50 CONVECTION; DAY FLUCTUATIONS; MADDEN-JULIAN NINO OSCILLATION; PACIFIC; PRECIPITATION; SOUTHERN TEMPERATURE TEMPORAL TROPICAL VARIABILITY; VARIATIONS; %N D11 %P 14941--14962 %T Wavelet analysis of covariance with application to atmospheric time series %U http://staff.washington.edu/dbp/PDFFILES/wavcov.pdf %V 105 %X Multiscale analysis of univariate time series has appeared in the literature at an ever increasing rate. Here we introduce the multiscale analysis of covariance between two time series using the discrete wavelet transform. The wavelet covariance and wavelet correlation are defined and applied to this problem as an alternative to traditional cross-spectrum analysis. The wavelet covariance is shown to decompose the covariance between two stationary processes on a scale by scale basis. Asymptotic normality is established for estimators of the wavelet; covariance and correlation. Both quantities are generalized into the wavelet cross covariance and cross correlation in order to investigate possible lead/lag relationships. A thorough analysis of interannual variability for the Madden-Julian oscillation is performed using a 35+ year record of daily station pressure series. The time localization of the discrete wavelet transform allows the subseries, which are associated with specific physical time scales, to be partitioned into both seasonal periods (such as summer and winter) and also according to El Nine-Southern Oscillation (ENSO) activity, Differences in variance and correlation between these periods may then be firmly established through statistical hypothesis testing. The daily station pressure series used here show clear evidence of increased variance and correlation in winter across Fourier periods of 16-128 days, During warm episodes of ENSO activity, a reduced variance is observed across Fourier periods of 8-512 days for the station pressure series from Truk Island and little or no correlation between station pressure series for the same periods.

@article{Whitcher.Guttorp.ea2000, abstract = {Multiscale analysis of univariate time series has appeared in the literature at an ever increasing rate. Here we introduce the multiscale analysis of covariance between two time series using the discrete wavelet transform. The wavelet covariance and wavelet correlation are defined and applied to this problem as an alternative to traditional cross-spectrum analysis. The wavelet covariance is shown to decompose the covariance between two stationary processes on a scale by scale basis. Asymptotic normality is established for estimators of the wavelet; covariance and correlation. Both quantities are generalized into the wavelet cross covariance and cross correlation in order to investigate possible lead/lag relationships. A thorough analysis of interannual variability for the Madden-Julian oscillation is performed using a 35+ year record of daily station pressure series. The time localization of the discrete wavelet transform allows the subseries, which are associated with specific physical time scales, to be partitioned into both seasonal periods (such as summer and winter) and also according to El Nine-Southern Oscillation (ENSO) activity, Differences in variance and correlation between these periods may then be firmly established through statistical hypothesis testing. The daily station pressure series used here show clear evidence of increased variance and correlation in winter across Fourier periods of 16-128 days, During warm episodes of ENSO activity, a reduced variance is observed across Fourier periods of 8-512 days for the station pressure series from Truk Island and little or no correlation between station pressure series for the same periods.}, added-at = {2011-09-01T13:26:03.000+0200}, author = {Whitcher, B. and Guttorp, P. and Percival, D. B.}, biburl = {https://www.bibsonomy.org/bibtex/2b79dcfc82631a2a8109469c4d7e86572/procomun}, c1 = {EURANDOM, NL-5600 MB Eindhoven, Netherlands.EOLEOLUniv Washington, Dept Stat, Seattle, WA 98195 USA.EOLEOLUniv Washington, Appl Phys Lab, Seattle, WA 98195 USA.EOLEOLMathSoft Inc, Seattle, WA USA.}, file = {Whitcher.Guttorp.ea2000.pdf:Whitcher.Guttorp.ea2000.pdf:PDF}, ga = {326LB}, interhash = {3aba8d48b57736a5cb117f3f2a9a10ba}, intrahash = {b79dcfc82631a2a8109469c4d7e86572}, j9 = {J GEOPHYS RES-ATMOS}, ji = {J. Geophys. Res.-Atmos.}, journal = {Journal of Geophysical Research-atmospheres}, keywords = {40-50 CONVECTION; DAY FLUCTUATIONS; MADDEN-JULIAN NINO OSCILLATION; PACIFIC; PRECIPITATION; SOUTHERN TEMPERATURE TEMPORAL TROPICAL VARIABILITY; VARIATIONS;}, la = {English}, month = jun, nr = {42}, number = {D11}, owner = {oscar}, pa = {2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA}, pages = {14941--14962}, pg = {22}, pi = {WASHINGTON}, publisher = {Amer Geophysical Union}, rp = {Whitcher, B, EURANDOM, Postbus 513, NL-5600 MB Eindhoven, Netherlands.}, sc = {Meteorology \& Atmospheric Sciences}, sn = {0747-7309}, tc = {42}, timestamp = {2011-09-02T08:25:25.000+0200}, title = {Wavelet analysis of covariance with application to atmospheric time series}, url = {http://staff.washington.edu/dbp/PDFFILES/wavcov.pdf}, ut = {ISI:000087736000043}, volume = 105, year = 2000 }