A Python-based diagnostics package is currently being developed by the ARM Infrastructure Team to facilitate the use of long-term high-frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, and precipitation. This diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison. The ARM observational data constitute the core content of the diagnostics package. These data products include two types of data sets: 1. Observational data: we use long-term data sets available at SGP, NSA, and TWP to build representative climatology. 2. CMIP5 climate model simulation data sets: these are auxiliary data sets for climate model evaluation.
The Python-based diagnostics package is available at: https://github.com/ARM-DOE/arm-gcm-diagnostics