Past severe droughts over North America have led to massive water shortages and increases in wildfire frequency. Triggering sources for multi-year droughts in this region include randomly occurring atmospheric blocking patterns, ocean impacts on atmospheric circulation, and climate's response to anthropogenic radiative forcings. A combination of these sources translates into a difficulty to predict the onset and length of such droughts on multi-year timescales. Here we present results from a new multi-year dynamical prediction system that exhibits a high degree of skill in forecasting wildfire probabilities and drought for 10-23 and 10-45 months lead time, which extends far beyond the current seasonal prediction activities for southwestern North America. Using a state-of-the-art earth system model along with 3-dimensional ocean data assimilation and by prescribing the external radiative forcings, this system simulates the observed low-frequency variability of precipitation, soil water, and wildfire probabilities in close agreement with observational records and reanalysis data. The underlying source of multi-year predictability can be traced back to variations of the Atlantic/Pacific sea surface temperature gradient, external radiative forcings, and the low-pass filtering characteristics of soils. Over the past six years, several regions in North America have experienced severe drought conditions. Their impacts cover a wide range of sectors such as agriculture, energy, food security, forestry, drinking water, and tourism 1, 2. Unusually dry and hot conditions were reported for Texas and Mexico in 2010-2011 3 , for the Great Plains in 2012 4 , and for California in 2011-2014 5, 6. The economic damage associated just with the recent California drought has been estimated at ~2.2 billion United States (US) Dollars and a loss of ~17,000 jobs 7. Successful water resource management that relies on knowledge of the present and future hydroclimatic conditions is crucial for mitigating the climate-driven drought risks. Even though the atmosphere has a short dynamical memory of less than several weeks, its evolution is partly affected by slowly varying sea surface temperature (SST) conditions. In the low-frequency range, atmospheric variability is modulated by more predictable climate phenomena such as the El Niño-Southern Oscillation (ENSO) 8 , the Pacific Decadal Oscillation (PDO) 9 , the Atlantic/Pacific SST contrast 10, 11 , and the Atlantic Multidecadal Oscillation 12, 13. The ratio of internally generated atmospheric variability and SST-forced variability thus limits the potential prediction horizon of monthly to seasonally averaged rainfall changes to less than 1 year 14-16. However, there are many land systems (e.g., soils, water reservoirs, vegetation, and perennial snowpack) that effectively filter out the high-frequency rainfall variability and therefore exhibit longer persistence as a result of natural time integration of atmospheric signals 17, 18. Consequently, this low-pass filtering effect enhances the cont...
[1] The ability of the Hadley Centre Coupled Model, version 3 (HadCM3) ocean-atmosphere general circulation model to represent the mechanisms linking the El Niño-Southern Oscillation (ENSO) and drought in the United States is investigated. Rotated principal components analyses of self-calibrating Palmer drought severity index data are used to categorize the dominant modes of summer drought variability in the observed climate record and in a 250-year period of a HadCM3 control run. A similar mode of large-scale drought variability is identified in both data sets that is correlated with ENSO variability: a monopolar pattern across the continental interior, centered over the southern states. HadCM3 successfully reproduces the displacement of the midlatitude jet streams during ENSO events, a mechanism related to U.S. drought variability, but the model appears to be less realistic in its simulation of the influence of Rossby wave teleconnections on drought, which is possibly due to limitations in its simulation of ENSO in the equatorial Pacific. Despite this we conclude that HadCM3's simulation of the link between ENSO and U.S. drought is sufficiently realistic for it to be used in further studies of U.S. drought variability.
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