1 Tagging systematic errors arising from different components of dynamics and physics in forecast models T.N. Krishnamurti and Vinay Kumar Department of Meteorology, Florida State University, Tallahassee Fl 32306 USA 1. Introduction Factor separation, introduced by Stein and Alpert (1993), Alpert et al (2006) permits an explicit separation of atmospheric synergies among several salient features of a forecast model. They have exploited the factor separation method covering many scales of modeling to answer questions on issues such as the role of water and CO 2 for the understanding of global change. Their proposed method has many wide ranging applications, as are seen from the contents of this book. Our proposed study follows the same rationale in asking how one can sort out and tag errors that arise from different components of a non linear model during the evolution of weather or climate. Our findings on the errors of a forecast model that arise from different components of model physics and dynamics are summarized and are extended here