Using Weather Attribution for Robust Representation of Present and Future Extreme Weather Events
Weather attribution estimates the current and near future likelihood for a recently observed extreme weather event, like a drought or hurricane. It uses climate models, weather prediction models, and observed weather to determine how much more likely the observed event is today relative to the recent past, like the 1990s and 2000s. In this study, a statistical weather generator (WG) creates synthetic sequences of future precipitation, temperature, and potential evapotranspiration that represent the increased likelihood for three-month severe drought. An independent weather attribution study identified that three-month severe drought is five times more likely to occur today relative to recent historical conditions. The WG-simulated conditions portray a near future where historical extreme and severe drought are significantly more likely to occur. The climate description produced by this WG is representative of the weather attribution study and is significantly hotter, with lower expected soil moisture than the future climate description obtained from global circulation, i.e., climate, model (GCM) simulation results (by themselves).
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Incorporating Weather Attribution to Future Water Budget Projections
Abstract: Weather attribution is a scientific study that estimates the relative likelihood of an observed weather event occurring under different climate regimes. Water budget models are widely used tools that can estimate future water resource management and conservation conditions using daily weather forcing. A stochastic weather generator (WG) is a statistical model of daily weather sequences designed to simulate or represent a climate description. A WG provides a means to generate stochastic, future weather forcing to drive a water budget model to produce future water resource projections. Observed drought magnitude and human-induced climate change likelihood from a weather attribution study provide targets for WG calibration. The attribution-constrained WG approximately reproduces the five fold increase in probability attributed to observed drought magnitude under climate change. A future (2031–2060) climate description produced by the calibrated WG is significantly hotter, with lower expected soil moisture than the future description obtained from global climate model (GCM) simulation results. The attribution-constrained WG describes future conditions where historical extreme and severe droughts are significantly more likely to occur.