### Table 1. Declensions of English Nominals (from da Silva, 1809, p. 40)

"... In PAGE 2: ...2 be seen, for example, in a table of declinations provided in a Portuguese grammar of English from 1809 ( Table1 ; from da Silva, 1809, p. 40): Table 1.... ..."

### Table 1: List of mandatory data attributes for a post-analysis ODS le. See da Silva and Redder (1995) for description of attributes. Variable

"... In PAGE 36: ... These HDF compliant les are intended to serve as input and output for GEOS/DAS, and unify the old REPACK and del- les used at DAO. Table1 lists all the attributes available for each observation stored on a (post-analysis) ODS le. The data type index kt identi es the observed quantity (wind, temperature, etc.... ..."

### Table 2. Table of regression coefficients and D6BE values, and percent variance explained by each mode. The first 10 PC time series of sea level pressure anomaly have been re- gressed on each of the first 4 sea surface temperature anomaly PC time series. The left column represents the SSTA mode numbers. The upper row represents the SLPA mode numbers. The regression results are based on the 49-year (1945-1993) monthly sea surface temperature and wind anomalies by da Silva et al. (1994).

"... In PAGE 14: ... The SLPA pattern (Fig. 5) associated with the first SSTA mode is primarily the first CSLV of the SLPA field, and explains about 86% of the total variability in the first PC of the SSTA (see Table2 ). During the winters of odd years, a strong SLPA contrast exists between the eastern and the western sides of the Pacific.... In PAGE 16: ...Table2 ). During the initiation of the biennial cycle, there is no noticeable change in the SLPA field (Fig.... ..."

### Table 2. Table of D6BE values and percent variance explained by each predictor PC time series in the regression exercise. The first 10 normalized PC time series of the subsurface temperature anomaly fields in the tropical Pacific Ocean have been regressed on the PC time series of the low-frequency mode of the SSTA field. The upper row represents the mode numbers of subsurface temperature anomaly. The left column is the index and the depth of each subsurface layer. The sea surface and the subsurface temperatures are from da Silva et al. (1994) and Giese and Carton (1999), respectively.

### Table 3. Table of D6BE values and percent variance explained by each predictor PC time series in the regression exercise. The first 10 normalized PC time series of the subsurface temperature anomaly fields in the tropical Pacific Ocean have been regressed on the PC time series of the biennial mode of the SSTA field. The upper row represents the mode numbers of subsurface temperature anomaly. The left column is the index and the depth of each subsurface layer. The sea surface and the subsurface temperatures are from da Silva et al. (1994) and Giese and Carton (1999), respectively.

### Table 4. Table of D6BE values and percent variance explained by each predictor PC time series in the regression exercise. The first 10 normalized PC time series of the subsurface current vector anomaly fields in the tropical Pacific Ocean have been regressed on the PC time series of the low-frequency mode of the SSTA field. The upper row represents the mode numbers of subsurface temperature anomaly. The left column is the index and the depth of each subsurface layer. The sea surface and the subsurface current vectors are from da Silva et al. (1994) and Giese and Carton (1999), respectively.

### Table 5. Table of D6BE values and percent variance explained by each predictor PC time series in the regression exercise. The first 10 normalized PC time series of the subsurface current vector anomaly fields in the tropical Pacific Ocean have been regressed on the PC time series of the biennial mode of the SSTA field. The upper row represents the mode numbers of subsurface temperature anomaly. The left column is the index and the depth of each subsurface layer. The sea surface and the subsurface current vectors are from da Silva et al. (1994) and Giese and Carton (1999), respectively.

### Table 2. Total heap usage and number of garbage collections.

"... In PAGE 14: ...Lopes, Silva and Vasconcelos Table2 shows that TyCO uses more heap space than Pict in functional applications such as tak. The situation changes completely when we switch to programs with object based data-structures.... ..."