HR: 1020h
AN: PP52A-0657    [Abstracts]
TI: A Wavelet Approach to Reconstructing Near-Surface Temperature Time Series From Observations of Subsurface Temperatures at Several Meters Depth
AU: * Pan, F
EM: feifei.pan@ce.gatech.edu
AF: School of Civil and Environmental Engineering, Georgia Institute of Technology 790 Atlantic Drive , Atlanta, GA 30332-0355 United States
AU: Smerdon, J E
EM: jsmerdon@ldeo.columbia.edu
AF: Lamont Doherty Earth Observatory of Columbia University, 61 Route 9W P.O. Box 1000, Palisades, NY 10964 United States
AU: Stieglitz, M
EM: marc.stieglitz@ce.gatech.edu
AF: School of Civil and Environmental Engineering, Georgia Institute of Technology 790 Atlantic Drive , Atlanta, GA 30332-0355 United States
AU: Stieglitz, M
EM: marc.stieglitz@ce.gatech.edu
AF: School of Earth and Environmental Sciences, Georgia Institute of Technology 311 Ferst Drive, Atlanta, GA 30332-0355 United States
AU: Webster, P
EM: pjw@eas.gatech.edu
AF: School of Civil and Environmental Engineering, Georgia Institute of Technology 790 Atlantic Drive , Atlanta, GA 30332-0355 United States
AU: Webster, P
EM: pjw@eas.gatech.edu
AF: School of Earth and Environmental Sciences, Georgia Institute of Technology 311 Ferst Drive, Atlanta, GA 30332-0355 United States
AB: Here we demonstrate a method that uses wavelet analysis to reconstruct a near-surface temperature time series from subsurface temperature observations taken at depth. Our approach is as follows: (1) we apply a wavelet transform to a 3-m subsurface temperature time series and construct a wavelet-filtered time series over a continuous set of frequency bands ranging from 0.5 to 65 years; (2) we upward continue each wavelet-filtered time series to a near-surface depth by shifting the spectral component in each band backward in time and amplifying the amplitude using the steady-state solution of the one-dimensional thermal diffusion equation; (3) we reconstruct the near-surface temperature time series by summing the upward continued time series associated with each band; and (4) we optimize the reconstruction by repeating steps 1 through 3 over a range of thermal diffusivities to minimize the root mean square error between observation and reconstruction at the near-surface depth. The method is applied to data observed at Fargo, North Dakota, comprising 6938 daily time steps between 1 September 1981 and 31 August 1999. We reconstruct several near-surface depths and show the method to accurately reconstruct observed temperatures, therefore demonstrating the wavelet approach as a promising means of characterizing subsurface thermodynamics.
DE: 1610 Atmosphere (0315, 0325)
DE: 1616 Climate variability (1635, 3305, 3309, 4215, 4513)
DE: 1626 Global climate models (3337, 4928)
DE: 1631 Land/atmosphere interactions (1218, 1843, 3322)
DE: 4920 Dendrochronology
SC: Paleoceanography and Paleoclimatology [PP]
MN: Fall Meeting 2005