26 JAN 2022 (WED) 17:05-17:35

Reconstructing large-scale hydroclimatic information from tree-ring data

Mr ZHANG Xu PhD Student, Department of Geography, HKU


Reconstructing large-scale hydroclimatic information is of great significance for projecting how earth climate system will change under global warming. Tree-ring data, due to its precisely annual dating and high sensitivity to climatology, provides us invaluable records about the paleo-hydroclimatology with large spatial coverage. However, some concerns still exist in dendroclimatology that prevent us from accurately reconstructing large-scale hydroclimatic information. Both dynamic and thermodynamic mechanisms are incorporated in large-scale climate reconstructions, which may reduce the accuracy due to the heterogeneity of precipitation. The low-frequency variations were not fully captured in tree-ring chronologies due to the standardization, and may underestimate the magnitude of warming trend. Terrestrial water storage (TWS), a hydrological variable that was recently measured from satellites, has not been reconstructed from tree-ring data. Based on these research gaps, here we will propose new methods for tree-ring reconstructions and may shed light on these research gaps from following three works:

  1. The El Niño/Southern Oscillation (ENSO), a key mode of atmospheric circulation, will be reconstructed over the past millennium with the exclusive incorporation of thermodynamic mechanisms. Global temperature-sensitive tree-ring chronologies from PAGES2k network will be used as predictors. The response of ENSO to volcanic eruptions will be quantified from latitudinally and monthly resolved stratospheric aerosol optical depth dataset.

  2. North hemisphere (NH) temperature will be reconstructed from global tree-ring network. To maintain the low-frequency variations, we propose a regional constant age (RCA) method that maintain low-frequency climatic information without any standardization. The RCA chronologies in the regions where tree growth is sensitive to temperature will be derived. Finally, NH temperature will be reconstructed from the RCA chronologies and independently validated against low-resolution proxies, solar irradiance, and volcanic forcing.

  3. TWS is a hydrological variable that directly represent the ecological drought but has not been reconstructed over the past millennium. The tree-ring chronologies over contiguous United States and China will be collected as predictors, and we plan to reconstruct gridded TWS using point-by-point method. The drought and its relation to carbon growth will be analyzed based on our reconstruction.

The reconstruction of ENSO may guide us to mitigate climate change through artificially injecting aerosols into atmosphere. The new RCA method may advance TRW-based reconstructions with the inclusion of low-frequency variations and increase our confidence because of clear physical foundations. The reconstruction of TWS may better represent drought in the history from an ecological perspective.