David Meko

University of Arizona, USA

Biography

Dave Meko is an Associate Research Professor in the Tree-Ring Laboratory at the University of Arizona. He works mainly on application of networks of tree-ring sites to extend hydrologic time series. He has published tree-ring reconstructions of precipitation, streamflow and drought indices at spatial scales from continental down to the small watershed. Study areas include North America, North Africa, and the Middle East. He and his research team were awarded a Climate Science Paper Award by the California Department of Water Resources for their 2007 work extending the record of Colorado River flow to the medieval period.

Abstract: Dendrochronology and links to stream flow

Dendrochronology has been applied in many parts of the world to estimate hydrologic variability on timescales of decades to centuries. This variability becomes increasingly important as water managers grapple with water shortages imposed by increasing demand and limited supply, and attempt to deal with possible exacerbation of shortages by climate change. The Colorado River has historically been a focal point of tree-ring studies aimed at quantitative temporal extension of streamflow time series. Recent studies exploiting ring-width records in preserved dead wood highlight medieval Colorado River droughts of duration unmatched either in the instrumental gaged flow record or in shorter tree-ring reconstructions based primarily on living trees. The North American tree-ring networks suggest that some of the more severe and sustained Colorado River droughts of the past were also large in spatial extent, and that the drought footprint at times included the Sierra Nevada of California and the watershed of the Sacramento River. Reconstructions from tree rings have long been used to infer possible bias in streamflow statistics based on the snapshot of time represented by short gaged records. More recently, water managers have begun directly incorporating reconstructions probabilistically into river management models to assess sensitivity of management options to extreme scenarios of climate variation experienced in the past. A basic necessity for accurate and robust streamflow reconstruction is a well-replicated network of moisture-sensitive tree-ring sites sampling the important runoff-producing regions of a watershed. Challenges include identification of signals at very low frequencies (wavelengths longer than lifespans of the oldest trees), and optimal estimation of magnitudes of streamflow anomalies, especially during wet years and for small watersheds in arid regions.