The Surface Storm Tracks in Three CMIP5 Global Climate Models

James F Booth1, Young-Oh Kwon2, Justin Small3, Rym Msadek4 and Stanley Ko1, (1)CUNY City College of New York, New York, NY, United States, (2)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (3)National Center for Atmospheric Research, Boulder, CO, United States, (4)GFDL/NOAA Princeton University, Princeton, NJ, United States
Abstract:
The surface storm tracks have local maxima in the region of the oceanic western boundary currents (WBC) and play an important role in air-sea heat exchange. Additionally, the surface storm tracks offer a unique test for global climate models (GCMs), because their location and amplitude are determined by a combination of forcing from above, via the free tropospheric storm track, and below, via the sea surface temperature (SST), which is particularly difficult for coupled models to capture in the WBC regions. Therefore the current work is designed to analyze the biases in the surface storm tracks and their relationship with the other biases in the coupled models.

Using CMIP5 model output from the GFDL CM3, the NASA GISS ModelE2-R and the NCAR CESM1, the GCMs are compared with the storm tracks in the ERA-Interim reanalysis. The surface storm tracks are calculated as the standard deviation of the 10-meter meridional winds, after time-filtering the winds to retain only the synoptic variability. The analysis is carried out again for the 850-hPa meridional winds, to capture the free tropospheric storm tracks. At the global scale, the models do well at capturing the spatial structure and amplitude of the surface storm tracks. However, at the ocean basin scale, the modeled storm tracks differ with each other and with the reanalysis, in amplitude and spatial extent. The storm tracks in the CESM1 is stronger than those in the reanalysis, while the GFDL and GISS exhibit weaker storm tracks. It is also shown that the spatial distributions of the surface storm tracks in the models can be determined using only the free tropospheric storm tracks and the near surface stability. Biases in the positions of the modeled surface storm tracks correspond to biases in the modeled SST. However, a lag correlation analysis suggests that the short-term temporal variability of the surface storm track is driven by the variability in the free troposphere. On this result, the models and reanalysis strongly agree.

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