Drought duration and frequency in the U.S. Corn Belt during the last millennium (AD 992–2004)

Abstract

Drought is among the most costly natural hazards affecting the United States, averaging $6 to $8 billion annually in damages, primarily in crop losses. Mitigating the impacts of drought through planning and preparedness has the potential to save billions of dollars. We used a new long tree-ring chronology developed from the central U.S. to reconstruct annual drought and characterize past drought duration, frequency, and cycles in the U.S. Corn Belt region during the last millennium. This is the first paleoclimate reconstruction achieved with subfossil oak wood in the U.S. and increases the current dendroclimatic record in the central U.S. agricultural region by over 500 years. A tree ring-width drought response function was calibrated and verified against monthly instrumental Palmer Hydrologic Drought Index (PHDI) during the summer season (JJA). Separate reconstructions tailored to emphasize high-frequency and low-frequency variations indicate that drought conditions over the period of instrumental records (since 1895) do not exhibit the full range of variability, severity, or duration of droughts during the last millennium. For example, three years in the last millennium were drier than 1934, a classic Dust-Bowl year and the driest year of the instrumental period. Thirteen decadal to multidecadal droughts (i.e., >=10 years) occurred during the last millennium – the longest lasting sixty-one years and centered on the late twelfth century. Reconstructions exhibited quasi-periodicity at bidecadal and century-scale periods. Significant rhythms in drought were identified near 20-yr and 128-yr periods. The tree-ring drought reconstruction shows promise in providing new information about long-term climate variability in the agricultural regions that could potentially span multimillennia. We postulate that tree-ring chronologies (i.e., tree growth), thus far under-utilized in agricultural applications, have the potential to match contributions of instrumental climate data.