OS015-0013
Spatial Heterogeneity in ENSO Sea Surface Temperatures over the Last Millennium: new insights from paleoclimate data assimilation
Spatial Heterogeneity in ENSO Sea Surface Temperatures over the Last Millennium: new insights from paleoclimate data assimilation
Wednesday, 9 December 2020
Poster
Abstract:
Year-to-year changes in temperature and rainfall over the mid-latitudes are highly dependent on El Niño/Southern Oscillation (ENSO) events in the tropical Pacific. These extra-tropical impacts (teleconnections) are not always consistent between individual ENSO events, however, due to large atmospheric variability and the diversity of patterns of warming or cooling associated with each ENSO event. Here, we use the Last Millennium Reanalysis (LMR) and the Paleo Hydrodynamics Data Assimilation product (PHYDA) to assess the consistency of rainfall patterns associated with different types of ENSO events. The 1000-year span of these datasets allows us to significantly augment the number of ENSO events considered in the analysis. We employ several definitions for Central Pacific (CP) and Eastern Pacific (EP) El Niño to characterize teleconnection rainfall and evaluate stationarity in rainfall patterns over the last 1000 years. Differentiation of ENSO diversity is reconstruction- and index definition-dependent. Nevertheless, our results indicate increased CP frequency and EP intensity in the 20th century compared to the last 1000 years, in agreement with previous work. The reconstructed rainfall patterns show dry conditions across the northeastern and central U.S., and wet conditions over the southwestern U.S. during CP events; conversely, during EP events, wet conditions over the northeastern and central U.S. and dry conditions over the southwestern U.S. are amplified. Given that IPCC-class GCMs simulate more frequent CP El Niño and increased ENSO intensity in future projections, the expanded constraints on CP- and EP-rainfall patterns afforded by the paleoclimate data products provide independent validation for climate models, and constraints on medium-range hydroclimate prediction. This information informs mitigation strategies for climate extremes such as floods and droughts in the United States.