The El Niño–Southern Oscillation (ENSO) is the most important source of
global climate variability on interannual timescales and has substantial
environmental and socio-economic consequences. However, it is unclear how it
interacts with large-scale climate states over longer (decadal to centennial)
timescales. The instrumental ENSO record is too short for analysing long-term
trends and variability and climate models are unable to accurately simulate past ENSO
states. Proxy data are used to extend the record, but different
proxy sources have produced dissimilar reconstructions of long-term ENSO-like
climate change, with some evidence for a temperature–precipitation
divergence in ENSO-like climate over the past millennium, in particular
during the Medieval Climate Anomaly (MCA; AD ∼ 800–1300) and the Little
Ice Age (LIA; AD ∼ 1400–1850). This throws into question the stability
of the modern ENSO system and its links to the global climate, which has
implications for future projections. Here we use a new statistical approach
using weighting based on empirical orthogonal function (EOF) to create two new
large-scale reconstructions of ENSO-like climate change derived independently
from precipitation proxies and temperature proxies. The method
is developed and validated using model-derived pseudo-proxy experiments that
address the effects of proxy dating error, resolution, and noise to improve
uncertainty estimations. We find no evidence that temperature and
precipitation disagree over the ENSO-like state over the past millennium, but
neither do they agree strongly. There is no statistically significant
difference between the MCA and the LIA in either reconstruction. However, the
temperature reconstruction suffers from a lack of high-quality proxy records
located in ENSO-sensitive regions, which limits its ability to capture the
large-scale ENSO signal. Further expansion of the palaeo-database and
improvements to instrumental, satellite, and model representations of ENSO are
needed to fully resolve the discrepancies found among proxy records and
establish the long-term stability of this important mode of climatic
variability
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