De. Waliser et Wf. Zhou, REMOVING SATELLITE EQUATORIAL CROSSING TIME BIASES FROM THE OLR AND HRC DATASETS, Journal of climate, 10(9), 1997, pp. 2125-2146
The objective of this study is to examine the impacts from satellite e
quatorial crossing time (ECT) changes on the outgoing longwave radiati
on (OLR) and highly reflective cloud (HRC) datasets and to design appr
opriate and robust methods to remove these satellite-dependent biases.
The OLR record covers the period from lune 1974 to July 1996 and is o
n a 2.5 degrees grid extending from 30 degrees S to 30 degrees N over
the global Tropics. The HRC record covers the period from January 1971
to December 1987 and is on a 2 degrees grid extending from 25 degrees
S to 25 degrees N over the global Tropics. Rotated empirical orthogon
al function analysis (REOF) is performed on both the monthly OLR and H
RC anomalies to help distinguish between artificial modes of variabili
ty and those associated with real variability. Results from the analys
is show that significant errors are introduced by changes in the satel
lite ECT, and they appear differently in the two datasets. The primary
satellite-related bias in the OLR appears as the fourth REOF mode, wh
ich accounts for 4.4% of the OLR anomaly variance. Its spatial pattern
exhibits a strong surface signature over land, with the opposite sign
over many of the deep convective regions of the ocean. During some pe
riods, these biases result in widespread errors of over 10 W m(-2), wh
ich are sustained for several months to over a year. In other cases, t
he transition between satellites induces abrupt, artificial changes in
the OLR as high as 16 W m(-2). In the HRC, the satellite-related bias
appears as the leading two REOF modes, which account for 13.1% of the
HRC anomaly variance. The spatial patterns of the HRC biases are indi
cative of an overall change in the mean climatological convection patt
ern. The above results can be understood by considering the sampling a
nd radiometric characteristics of the OLR and HRC datasets. To remove
the satellite ECT biases, the REOF time series of the satellite-relate
d modes are modified by using the detailed knowledge of the satellite
ECTs so that only artificial variability related to the satellite chan
ges is captured and the natural variability is excluded. These modifie
d time series are used in conjunction with their associated spatial pa
tterns to compute the satellite-related artificial variability, which
is then removed from the two datasets. These datasets provide an impro
ved resource to study intraseasonal and longer timescale regional clim
ate variations, large-scale interannual variability, and global-scale
climate trends. Analyses of the long-term trends in both datasets show
that the satellite biases induce artificial trends in the data and th
at these artificial trends are reduced in the corrected datasets. Furt
her, each of the corrected datasets exhibits a trend in the tropical w
estern-central Pacific that appears spatially independent of the satel
lite biases and agrees with results of previous studies that indicate
an increase in precipitation has occurred in this region over the peri
od encompassed by these datasets.