Title: Climate Model Diagnostic Analyzer
Presenting Author: Seungwon Lee
Organization: Jet Propulsion Laboratory

Abstract:
Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from the Coupled Model Intercomparison Project Phase 5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. In response, we are developing a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system for the Earth science modeling and model analysis community. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA) and is built upon the current version of CMDA, which is the product of the research and technology development investments of several current and past NASA ROSES programs. We leverage the current technologies and infrastructure of CMDA and extend the capabilities of CMDA to address several technical challenges that the modeling and model analysis community faces in evaluating climate models. We utilize three technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology.