Sunday, 10 January 2016
Hall E ( New Orleans Ernest N. Morial Convention Center)
Due to complicated ocean / land topography and sparse data measurements, modeling of atmospheric processes over the Maritime Continent (MC) is notoriously difficult. Due to systematic biases, simply using reanalysis data set output as boundary conditions in smaller scale modeling may not produce reliable results. In this study, vertical thermodynamic profiles generated from the ERA-Interim and MERRA data sets are compared with radiosonde observations from several sites over the MC for the period 2005-2015. Clear biases were found in temperature and humidity in both the ERA-Interim and MERRA products over the MC. Following the reanalysis evaluation, an examination of the sounding data set is conducted for the purpose of exploring the dominant vertical temperature, humidity, and wind structures in the region. Principal Component Analysis (PCA) is employed to transform vertical patterns present in radiosonde data for these variables into typical thermodynamic profiles for the MC. This analysis is repeated for both MERRA and ERA-Interim data sets. The results indicate that biases may be effectively addressed if they are removed in a lower dimensional subspace, allowing for more realistic model simulations of atmospheric processes, particularly cloud development, convection, and precipitation over the MC.
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