Student Seminar: Melissa Gervais
Please join us tomorrow in Burnside 934 at 14:35 for a student seminar by Melissa Gervais. Abstract follows.
How Well is the Distribution of Precipitation Represented? Part I: Impacts of Station Density and Resolution Changes on Gridded Station Data
Precipitation is one of the most important variables to predict in future climate change owing to the socio-economic implications for water resources. However, it has historically been a very challenging variable for climate models to predict. Newer versions of Community Climate System Model (CCSM) from the National Center for Atmospheric Research (NCAR) have seen great improvements in their representation of the distribution of precipitation, with results now very close to observations (Gent 2011). The accuracy of precipitation observations used to validate the GCM output is thus becoming increasingly important. Results will be presented from the first of two studies on examining the ability of observations, reanalysis, the CCSM4 fully coupled model, and the NCAR Community Atmosphere Model (CAM5), to represent the distribution of precipitation. Here, we focus on the accuracy of interpolating station data in terms of the method of interpolation and the station density.
Station data from the Global Historical Climatology Network – Daily Version 1.0, within the United States, will be used to create and test gridded precipitation products. The goal is firstly to examine what the impact of gridding station data is on the precipitation statistics and whether the gridding method used is important. Secondly, an experiment will be conducted to determine how dense an observation network needs to be, in different climatic regions, in order to produce an accurate distribution of precipitation. This allows us to identify regions where station density is not high enough to trust the gridded precipitation data for validating GCMs.