4.5 Article

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

Journal

CLIMATE OF THE PAST
Volume 13, Issue 12, Pages 1851-1900

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/cp-13-1851-2017

Keywords

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Funding

  1. US National Science Foundation through the National Center for Atmospheric Research
  2. US National Science Foundation [AGS-1502150, AGS-1303976, AGS-1433551, AGS-1602564, AGS-1501856, AGS-1243125, AGS-1243107, AGS-1404003, AGS-1243204, AGS-1401400, AGS-1602581, AGS-1502830, AGS-1203785, AGS-1602920, OCE-1502832]
  3. Australian Research Council [SR140300001, FL100100195, DECRA DE16010092]
  4. National Natural Science Foundation of China [41305069, 41675082]
  5. Jiangsu Collaborative Innovation Center for Climate Change
  6. German Federal Ministry of Education and Research (BMBF)
  7. JPI-Climate/Belmont Forum [FKZ: 01LP1607B]
  8. DFG-Research Center/Cluster of Excellence
  9. Swedish Science Council (VR) [2012-5246]
  10. Swiss National Science Foundation
  11. Brown Institute for Environment and Society
  12. Lamont-Doherty Postdoctoral Fellowship and Earth Institute Postdoctoral Fellowship programs of Columbia University
  13. NOAA Climate and Global Change Postdoctoral Fellowship Program
  14. Directorate For Geosciences
  15. Div Atmospheric & Geospace Sciences [1243107, 1433408, 1619827] Funding Source: National Science Foundation
  16. Directorate For Geosciences
  17. Div Atmospheric & Geospace Sciences [1401400, 1404003, 1243204, 1623727] Funding Source: National Science Foundation
  18. Division Of Earth Sciences
  19. Directorate For Geosciences [1440015] Funding Source: National Science Foundation

Ask authors/readers for more resources

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

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