CCPP-ARM GCM Analysis of Tendency Errors (CAGATE): Part I Method

Potter, G.L.(a), Boyle, J.S.(a), Cederwall, R.T.(a), Fiorino, M.(a), Hnilo, J.J.(a), Phillips, T.J.(a), and Williamson, D.(b), Lawrence Livermore National Laboratory (a), National Center for Atmospheric Research (b)
Twelfth Atmospheric Radiation Measurement (ARM) Science Team Meeting

We present a methodology to diagnose GCM errors by using NWP analyses to initialize a climate model. The analysis is used as input in conjunction with ARM data to study the initial model drift (6-36 hours) from the observations. Simply put, a climate model is used in a weather forecast mode to see how quickly it drifts from the observed weather and detailed observations provided by the ARM program. This approach can be used to improve parameterizations responsible for models errors on longer time scales in much the same way that NWP centers use short-range forecast verifications to improve their models. The goal is to make the techniques developed available to all modeling groups in an effort to improve climate models. This poster presents a methodology using the new Community Atmospheric Model (CAM) from the Community Climate System Model (CCSM). This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under Contract No. W-7405-Eng-48.

Note: This is the poster abstract presented at the meeting; an extended version was not provided by the author(s).