REMOVING SATELLITE EQUATORIAL CROSSING TIME BIASES FROM THE OLR AND HRC DATASETS

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.