Geoscience Reference
In-Depth Information
INTERANNUAL VARIATIONS IN PACIFIC SST
DEVIATIONS THROUGH AVHRR
∗
JUN YU
†
and PER GLOERSEN
‡
†
Department of Mathematics and Statistics, University of Vermont
Burlington, VT 05401, USA
‡
NASA/Goddard Space Flight Center
Greenbelt, MD 20771, USA
We study variability of Pacific sea surface temperature (SST) from 1985 to 1997
utilizing the data derived from the Advanced Very High-Resolution Radiometer
(AVHRR). In order to enhance our analysis on the SST, we preprocess our data
to derive Pacific SST deviations. Then, we study Hoffmueller diagrams for the
SST deviations along different paths in the Pacific. Both 1987 and 1997-1998
El Nino events as well as the 1984-1985, 1989 and 1996 La Nina events are
clearly depicted. Hoffmueller diagram along a path in the North Pacific shows
an eastward moving trough during 1986 to 1989 and the pattern is followed
by moving crests up to about 1993. Finally, we compare our current results
with those from earlier studies using the NASA data of scanning multichannel
microwave radiometer (SMMR).
1. Introduction
Climate variability in oceans has received considerable attention in recent
years (see for example, Refs. 1-4). Global SST/Sea Level Pressure waves
as well as basin-scale upper ocean temperature anomalies were studied in
Refs. 5-7. Troposphere thermal and vorticity budgets were studied in Ref. 8,
showing El Nino Southern Oscillations (ENSO) as one of the two dominant
signals in Pacific Decadal Oscillation in the mid-latitude North Pacific
Ocean from 1979 through 2001. Here, satellite measurements of SST are
based on techniques in which spaceborne infra-red and microwave radiome-
ters detect thermally emitted radiation from the ocean surface (see Ref. 9).
Procedure for SST retrievals from infrared sensors was developed in Ref. 10
for the NOAA polar-orbiting AVHRR. Application of SST in computing the
latent heat flux can be found in Ref. 11. Reference 12 described the calibra-
tion and processing procedure for obtaining SST data from the SMMR on
∗
This work is supported by the Vermont-NASA EPSCoR Program and the University
of Vermont.
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