Abstract
[1] Climate metrics are becoming a more widespread tool used in global circulation model (GCM) evaluation as well as climate change projections. In their more simple form they provide a quick overview of the performance of a large ensemble of GCM simulations such as the CMIP3 archive of coupled ocean-atmosphere GCMs. Most existing metrics focus on the comparison of fields at each grid point. We present here a complementary metric which targets structures as a whole (patterns). The methodology is based on a pattern matching technique used previously in numerical weather prediction and has been modified for the analysis of mean climate fields. The resulting error decomposition allows for a more detailed assessment of the field structure with regard to errors in placement, rotation, volume, and pattern. The technique is applied to two observational rainfall data sets and GCM simulations from the CMIP3 archive for seasonal rainfall structures over the South Pacific Convergence Zone.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
