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...

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The Earth’s temperature has increased 0.6 °C over the last 100 years, and further climate change is predicted to potentially raise it by 3.5 °C over the next century. More than half of the global annual net primary production of biomass is estimated to occur in the tropics, especially tropical evergreen forest. In temperate forests, increasing temperature may extend the non-frost growing season, and thus increase the CO2 sequestration rate, but some authors have also suggested a negative impact of warming in tropical forests from decreased photosynthetic activity. Using the PL model (Ricker and del Río 2004), we forecast growth of two Mexican tree species after climate warming. The model predicts the high-mountain species Pinus hartwegii Lindl. to decrease its expected relative growth throughout its lifetime by 10.6% as a consequence of a 0.6 °C temperature increase; in contrast, the tropical rainforest species Diospyros digyna Jacq. is predicted to increase its expected relative growth throughout its lifetime by 25.4%. The key factor appears to be the expected relationship between temperature and precipitation, rather than temperature alone. While one cannot expect a universal response across sites, some standing tropical rainforests such as those at Los Tuxtlas in Mexico may constitute a carbon sink in a changing climate.

Influencia del clima en el crecimiento radial en cuatro especies de coníferas en la sierra de San Antonio Peña Nevada (Nuevo León, México) Climatic inflluence on radial growth in four conifer species in the