Quantification of Land-Atmosphere Coupling and Implications for Drought Persistence In Observations and Model Simulations of 20th Century Climate and 21st Century Climate Change

Of all recurring natural disasters, long-term drought is one of the most devastating and costly due to large spatial extent and often long duration. The mechanisms responsible for the maintenance of long-term droughts are not well understood, however many drought analyses allege the importance of land-atmosphere feedbacks and speculate that these feedbacks will amplify changes in the hydrological cycle in the presence of climate change, increasing drought severity. A statistical lagged correlation method is applied to IPPC model and observed precipitation and evaporation data to quantify JJA land-atmosphere coupling based on a positive feedback between evaporation and later precipitation. Results of this statistical method are broadly consistent with results of other land-atmosphere coupling analyses with some important differences, most notably in the Sahara and Arabian deserts. In addition, drought analysis is conducted using a percentile scheme to quantify JJA drought frequency and drought persistence. The relationship between land-atmosphere coupling and drought persistence is analyzed by plotting drought persistence against land-atmosphere coupling; the result shows a positive linear relationship in three regions examined in which model drought persistence increases with land-atmosphere coupling strength. Enabled with this relationship for 20 th century model data, we examine drought in IPCC simulations of 21 st century climate to determine if land-atmosphere coupling is strongly correlated with increasing drought frequency. Surprisingly, no significant relationship is found, indicating that land-atmosphere coupling does not contribute strongly to future drought as many previous studies have suggested, and that other, more large-scale climate processes— poleward shifts in stormtracks, and changes in land-ocean temperature contrasts—are primarily responsible for changes in hydrological extremes in climate change simulations.