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Future Changes in High-Risk Synoptic Weather Patterns

PI: David Grass
Institution: Columbia University
Objective: Test whether the character, frequency, and persistence of high-risk weather classes change during the period beginning in 1961 and ending in 2100.


For the area surrounding New York City and Santiago, Chile, apply a synoptic typing procedure to daily NCEP-DOE Reanalysis II data, assigning each day from 1981 to 2000 to a class with homogenous weather conditions. Separate analyses will be carried out for the summer months and the winter months. Identify high-mortality and/or high air pollution weather types based on daily mortality counts and pollution levels.

Apply a linear discriminant function to daily data output from four models from the CMIP3 multi-model dataset, assigning each day in the years 1961-2000, 2046-2065 and 2081-2100 to an existing weather class defined using the NCEP reanalysis data. Four ICCP models will be used selected on the basis of which models are minimally biased and adequately capture the intra-annual and inter-annual variability in surface temperature, humidity, and sea-level pressure when compared to NCEP reanalysis data and interpolated weather station data.

The discriminate functionís ability to identify high risk weather classes (using NCEP data as a proxy for the CMIP3 data) will be validated by applying the classification procedure to the 2001-2004 period which was not used to determine the discriminant linear functions but for which mortality and air pollution data are available.

The four 20-year periods (1961-1980, 1981-2000, 2046-2065, and 2081-2100) will be compared to determine how the character, the frequency of occurrence, or the persistence of high risk weather classes changes over time. The extent of these changes will be compared under different emissions scenarios (A2, A1B, and B1). Forecasts of weather and air-pollution related mortality will be made with the assumption that the weather-air pollution-mortality dose-response relationships will not change over time (i.e. no adaptation).


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    Lawrence Livermore National Laboratory  |  Physical & Life Sciences Directorate