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Chapter 6: Analysing the Boreal Summer Relationship
3.0% level, suggesting. Northern Hemisphere extratropical circulation is
probably related to Sabel rainfall variations. The field significance of
the tropical Pacific and tropical Indian oceans is very high. The relatively lower significance for the tropical Atlantic is probably due to the
different Atlantic atmospheric patterns that occur in different types of
droughts and wet years in the Sahel (Janicot, 1992bj and see Figure 6.7
later). Such a situation reduces the linear correlation over all years between Sahel rainfall and atmospheric circulation in the tropical Atlantic
sector.
b) Nature of the Relationships
Through the tropics, the correlation patterns (Figure 6.6) suggest Sahel rainfall is linked to SST and marine atmospheric variability associated with SST
p2 and SST Pft. Indeed, the correlation between each of the EOFs and Sahel
rainfall is statistically significant (Table 6.3). In the tropical Pacific, the SST
correlations (Figure 6.6a) are very positive in the western equatorial region.
This suggests adeparture from the SST p2 pattern (Figure 6.1a), which has
weak weights in the western Pacific. It was noted earlier that the western
Pacific was a strong candidate for triggering tropic-wide atmospheric teleconnections. The correlation patterns support this idea. However, the strong
correlations in the eastern Pacific with SST and SLP (Figure 6.6a,b) are also
consistent with an infiuence of a direct circulation from the eastern Pacific
to the Atlantic and West Africa.
Outside the tropics, there are two potentially important teleconnections for
Europe. Firstly, Sahel rainfall correlates positively with SST and negatively
with SLP in the eastern Mediterranean. Secondly, Sahel rainfall correlates
with low SLP near and to the north of the UK. Both these connections require
theoretical and numerical model investigation.
Janicot (1992b) argued that the tropical Atlantic marine relationships with
Sahel rainfall were conditional upon whether rainfall anomalies on the Guinea
Coast were of opposite sign to those in the Sahel (DIPOLE years) or were
the same sign (NO DIPOLE years). To show that not just the Atlantic
but the global relationships with marine variability are different in DIPOLE
compared to NO DIPOLE years, Sahel rainfall has been correlated with SLP
in DIPOLE years (Figure 6.7a) and NO DIPOLE years (Figure 6.7b). In
DIPOLE years, correlations are strongest in the tropical South Atlantic where
the pattern is similar (but sign inverted) to the SLP - SST pA map (Figure
6.4a), supporting the idea that positive (negative) values of SST pA force
more (less) rain on the Guinea Coast and less (more) rain in the Sahel (see
Table 6.3). In NO DIPOLE years, the SLP correlations (Figure 6.7b) are
similar (but sign inverted) to those with SST p2 (Figure 6.2a), suggesting
that SST p2 tends to be associated with rainfall anomalies of the same sign
over West Africa. This also suggests that SST pA and SST p2 explain an
independent fr action of Sahel rainfall variance. One way to test this is using
Chapter 6: Analysing the Boreal Summer Relationship
3.0% level, suggesting. Northern Hemisphere extratropical circulation is
probably related to Sabel rainfall variations. The field significance of
the tropical Pacific and tropical Indian oceans is very high. The relatively lower significance for the tropical Atlantic is probably due to the
different Atlantic atmospheric patterns that occur in different types of
droughts and wet years in the Sahel (Janicot, 1992bj and see Figure 6.7
later). Such a situation reduces the linear correlation over all years between Sahel rainfall and atmospheric circulation in the tropical Atlantic
sector.
b) Nature of the Relationships
Through the tropics, the correlation patterns (Figure 6.6) suggest Sahel rainfall is linked to SST and marine atmospheric variability associated with SST
p2 and SST Pft. Indeed, the correlation between each of the EOFs and Sahel
rainfall is statistically significant (Table 6.3). In the tropical Pacific, the SST
correlations (Figure 6.6a) are very positive in the western equatorial region.
This suggests adeparture from the SST p2 pattern (Figure 6.1a), which has
weak weights in the western Pacific. It was noted earlier that the western
Pacific was a strong candidate for triggering tropic-wide atmospheric teleconnections. The correlation patterns support this idea. However, the strong
correlations in the eastern Pacific with SST and SLP (Figure 6.6a,b) are also
consistent with an infiuence of a direct circulation from the eastern Pacific
to the Atlantic and West Africa.
Outside the tropics, there are two potentially important teleconnections for
Europe. Firstly, Sahel rainfall correlates positively with SST and negatively
with SLP in the eastern Mediterranean. Secondly, Sahel rainfall correlates
with low SLP near and to the north of the UK. Both these connections require
theoretical and numerical model investigation.
Janicot (1992b) argued that the tropical Atlantic marine relationships with
Sahel rainfall were conditional upon whether rainfall anomalies on the Guinea
Coast were of opposite sign to those in the Sahel (DIPOLE years) or were
the same sign (NO DIPOLE years). To show that not just the Atlantic
but the global relationships with marine variability are different in DIPOLE
compared to NO DIPOLE years, Sahel rainfall has been correlated with SLP
in DIPOLE years (Figure 6.7a) and NO DIPOLE years (Figure 6.7b). In
DIPOLE years, correlations are strongest in the tropical South Atlantic where
the pattern is similar (but sign inverted) to the SLP - SST pA map (Figure
6.4a), supporting the idea that positive (negative) values of SST pA force
more (less) rain on the Guinea Coast and less (more) rain in the Sahel (see
Table 6.3). In NO DIPOLE years, the SLP correlations (Figure 6.7b) are
similar (but sign inverted) to those with SST p2 (Figure 6.2a), suggesting
that SST p2 tends to be associated with rainfall anomalies of the same sign
over West Africa. This also suggests that SST pA and SST p2 explain an
independent fr action of Sahel rainfall variance. One way to test this is using