• Ayrault, F., , F. Lalaurette, , A. Joly, , and C. Loo, 1995: North Atlantic ultra high frequency variability. Tellus, 47A , 671696.

  • Blackmon, M. L., 1976: A climatological spectral study of the 500 mb geopotential height of the Northern Hemisphere. J. Atmos. Sci., 33 , 16071623.

    • Search Google Scholar
    • Export Citation
  • Blackmon, M. L., , J. M. Wallace, , N. C. Lau, , and S. L. Mullen, 1977: An observational study of the Northern Hemisphere wintertime circulation. J. Atmos. Sci., 34 , 10401053.

    • Search Google Scholar
    • Export Citation
  • Blender, R., , K. Fraedrick, , and F. Lunkeit, 1997: Identification of cyclone-track regimes in the North Atlantic. Quart. J. Roy. Meteor. Soc., 123 , 727741.

    • Search Google Scholar
    • Export Citation
  • Esbensen, S. K., , and R. W. Reynolds, 1981: Estimating monthly averaged air–sea transfers of heat and momentum using the bulk aerodynamic method. J. Phys. Oceanogr., 11 , 457465.

    • Search Google Scholar
    • Export Citation
  • LabSea Group, 1998: The Labrador Sea Deep Convection Experiment. Bull. Amer. Meteor. Soc., 79 , 20332058.

  • Lazier, J. N. R., 1980: Oceanographic conditions at Ocean Weather Ship Bravo, 1964–1974. Atmos.–Ocean, 18 , 227238.

  • Mann, M. E., , and J. Lees, 1996: Robust estimation of background noise and signal detection in climatic time series. Climatic Change, 33 , 409445.

    • Search Google Scholar
    • Export Citation
  • Marshall, J., , and F. Schott, 1999: Open-ocean convection: Observations, theory and models. Rev. Geophys., 37 , 164.

  • Moore, G. W. K., , M. C. Reader, , J. York, , and S. Sathiyamoorthy, 1996: Polar lows in the Labrador Sea: A case study. Tellus, 48A , 1740.

    • Search Google Scholar
    • Export Citation
  • Moore, G. W. K., , K. Alverson, , and I. A. Renfrew, 2002: A reconstruction of the air–sea interaction associated with the Weddell Polynya. J. Phys. Oceanogr., 32 , 16851698.

    • Search Google Scholar
    • Export Citation
  • Renfrew, I. A., , and G. W. K. Moore, 1999: An extreme cold-air outbreak over the Labrador Sea: Roll vorticies and air–sea interaction. Mon. Wea. Rev., 127 , 23792394.

    • Search Google Scholar
    • Export Citation
  • Rogers, J. C., 1997: North Atlantic storm track variability and its association to the North Atlantic Oscillation and climate variability of northern Europe. J. Climate, 10 , 16351647.

    • Search Google Scholar
    • Export Citation
  • Sathiyamoorthy, S., , and G. W. K. Moore, 2002: Buoyancy flux at Ocean Weather Station Bravo. J. Phys. Oceanogr., 32 , 458474.

  • Sawyer, J. S., 1970: Observational characteristics of atmospheric fluctuations with a time scale of a month. Quart. J. Roy. Meteor. Soc., 96 , 610625.

    • Search Google Scholar
    • Export Citation
  • Smith, S. D., , and F. W. Dobson, 1984: The heat budget at Ocean Weather Station Bravo. Atmos.–Ocean, 22 , 122.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 110 110 7
PDF Downloads 11 11 5

Quantifying Temporal Variance in High-Latitude Air–Sea Interactions

View More View Less
  • 1 Department of Physics, University of Toronto, Toronto, Ontario, Canada
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

A novel way of quantifying the variance of a time series is presented. The method first involves filtering the time series using filters with different temporal characteristics, and then using a moving window to calculate the variances in each filtered time series. The use of a moving window allows the original temporal resolution to be retained, as well as allowing one to study how the variance changes with time. Air–sea interaction time series from Ocean Weather Station (OWS) Bravo in the Labrador Sea are analyzed as an example. High-pass, bandpass, and low-pass filters are used to isolate the diurnal signal, the storm/cyclone signature, and the weather regime transition signal, respectively. The variance during the winter months is found to be strongly influenced by weather systems in the bandpass and the low-pass frequency range. The variance during the summer months, on the other hand, is dominated by the shortwave radiation in the high-pass frequency range.

Corresponding author address: Dr. Sudharshan Sathiyamoorthy, Dept. of Physics, University of Toronto, 60 St. George St., Toronto, ON M5S 1A7, Canada. Email: sathy@atmosp.physics.utoronto.ca

Abstract

A novel way of quantifying the variance of a time series is presented. The method first involves filtering the time series using filters with different temporal characteristics, and then using a moving window to calculate the variances in each filtered time series. The use of a moving window allows the original temporal resolution to be retained, as well as allowing one to study how the variance changes with time. Air–sea interaction time series from Ocean Weather Station (OWS) Bravo in the Labrador Sea are analyzed as an example. High-pass, bandpass, and low-pass filters are used to isolate the diurnal signal, the storm/cyclone signature, and the weather regime transition signal, respectively. The variance during the winter months is found to be strongly influenced by weather systems in the bandpass and the low-pass frequency range. The variance during the summer months, on the other hand, is dominated by the shortwave radiation in the high-pass frequency range.

Corresponding author address: Dr. Sudharshan Sathiyamoorthy, Dept. of Physics, University of Toronto, 60 St. George St., Toronto, ON M5S 1A7, Canada. Email: sathy@atmosp.physics.utoronto.ca

Save