  A widely used indicator of Indian summer monsoon variability is the
June-July-August-September (JJAS) rainfall rate averaged over all of India
(AIR). But AIR's relationship with the spatial extent of dry or wet anomalies
across India is contested, its relationship with El Nino-Southern Oscillation
(ENSO) has weakened since the early 20th century, and its relationship with the
Equatorial Indian Ocean Oscillation (EQUINOO) has only been examined for the
late 20th and 21st centuries. We explore these issues using long-duration
(1901-2020), sea surface temperature, reanalysis, and high-resolution rainfall
($0.25^\circ\times0.25^\circ$) gridded rainfall datasets. AIR is highly
correlated ($r>0.95$) both with indices determined predominantly by raw
rainfall anomalies in the high-variance Central Monsoon Zone and Western Ghats
regions and with indices we define characterizing the spatial extent of
standardized rainfall anomalies across all of India: the high-rainfall regions
dictate AIR \emph{and} vary closely with the extent of drought or excess
rainfall over the subcontinent. The JJAS rainfall regression patterns for ENSO
and EQUINOO change in compensating ways from the pre-satellite to satellite
eras, such that a combined index, ENSINOO, is more stable and corresponds to
widespread drying or wetting. Because EQUINOO exhibits strong variance on daily
as well as seasonal timescales, however, it is not obvious to what extent its
seasonal-mean signal reflects a remotely forced teleconnection vs. the residual
of larger, shorter-timescale variability.
