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A reconstruction of global hydroclimate and dynamical variables over the Common Era.
Steiger, Nathan J; Smerdon, Jason E; Cook, Edward R; Cook, Benjamin I.
Affiliation
  • Steiger NJ; Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964, USA.
  • Smerdon JE; Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964, USA.
  • Cook ER; Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964, USA.
  • Cook BI; NASA Goddard Institute for Space Studies, New York, NY 10025, USA.
Sci Data ; 5: 180086, 2018 May 22.
Article in En | MEDLINE | ID: mdl-29786698
Hydroclimate extremes critically affect human and natural systems, but there remain many unanswered questions about their causes and how to interpret their dynamics in the past and in climate change projections. These uncertainties are due, in part, to the lack of long-term, spatially resolved hydroclimate reconstructions and information on the underlying physical drivers for many regions. Here we present the first global reconstructions of hydroclimate and associated climate dynamical variables over the past two thousand years. We use a data assimilation approach tailored to reconstruct hydroclimate that optimally combines 2,978 paleoclimate proxy-data time series with the physical constraints of an atmosphere-ocean climate model. The global reconstructions are annually or seasonally resolved and include two spatiotemporal drought indices, near-surface air temperature, an index of North Atlantic variability, the location of the intertropical convergence zone, and monthly Niño indices. This database, called the Paleo Hydrodynamics Data Assimilation product (PHYDA), will provide a critical new platform for investigating the causes of past climate variability and extremes, while informing interpretations of future hydroclimate projections.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Data Year: 2018 Document type: Article Affiliation country: United States Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Data Year: 2018 Document type: Article Affiliation country: United States Country of publication: United kingdom