6 research outputs found

    Causes and Implications of Extreme Atmospheric Moisture Demand during the Record-Breaking 2011 Wildfire Season in the Southwestern United States

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    In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May–July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies

    Correlations between components of the water balance and burned area reveal new insights for predicting forest fire area in the southwest United States

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    We related measurements of annual burned area in the southwest United States during 1984–2013 to records of climate variability. Within forests, annual burned area correlated at least as strongly with spring–summer vapour pressure deficit (VPD) as with 14 other drought-related metrics, including more complex metrics that explicitly represent fuel moisture. Particularly strong correlations with VPD arise partly because this term dictates the atmospheric moisture demand. Additionally, VPD responds to moisture supply, which is difficult to measure and model regionally due to complex micrometeorology, land cover and terrain. Thus, VPD appears to be a simple and holistic indicator of regional water balance. Coupled with the well-known positive influence of prior-year cold season precipitation on fuel availability and connectivity, VPD may be utilised for burned area forecasts and also to infer future trends, though these are subject to other complicating factors such as land cover change and management. Assuming an aggressive greenhouse gas emissions scenario, climate models predict mean spring–summer VPD will exceed the highest recorded values in the southwest in nearly 40% of years by the middle of this century. These results forewarn of continued increases in burned forest area in the southwest United States, and likely elsewhere, when fuels are not limiting

    Scalar and Multivariate Approaches for Optimal Network Design in Antarctica

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    Thesis (Master's)--University of Washington, 2014Observations are crucial for weather and climate, not only for daily forecasts and logistical purposes, for but maintaining representative records and for tuning atmospheric models. Here scalar theory for optimal network design is expanded in a multivariate framework, to allow for optimal station siting for full field optimization. Ensemble sensitivity theory is expanded to produce the covariance trace approach, which optimizes for the trace of the covariance matrix. Relative entropy is also used for multivariate optimization as an information theory approach for finding optimal locations. Antarctic surface temperature data is used as a testbed for these methods. Both methods produce different results which are tied to the fundamental physical parameters of the Antarctic temperature field
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