Data / Science Data Products / VAPs

ADCME

ADCME: ARM Diagnostics for Climate Model Evaluation

This VAP constitutes the core content of the ARM data-oriented diagnostics package –– a Python-based diagnostic package (ARM-DIAGS) that aims to facilitate the use of ARM data sets in climate model evaluation (Zhang et al. 2020). Currently, ARM-DIAGS is available at the ARM Southern Great Plain (SGP), North Slope of Alaska (NSA), and Tropical Western Pacific atmospheric observatories (TWP). Two types of data sets are included in the ADCME: 1) long-term high-frequency observational data for representative climatology computation and 2) the Coupled Model Intercomparison Project (CMIP5) climate model simulation data sets acting as a reference for other models to compare with. The observational data are derived from ARM Best Estimate (ARMBE) data products, ARM long-term continuous forcing data (VARANAL), ARM Cloud Retrieval Ensemble Data (ACRED), and other ARM value-added products (VAPs) for variables not included in the first three data sources.

The ARM-DIAGS serves as an easy entry point for climate modelers to compare their models with ARM observations. The ADCME is primarily used to support the ARM-DIAGS, which includes commonly used metrics for mean climate and diurnal and seasonal variability of selected important geophysical cloud and precipitation-related quantities as well as the process-oriented diagnostics, i.e., convection onset metrics.

The ARM data included in this product have gone through stringent data quality control and represent the ‘best’ estimate of the selected quantities. As noted above, multiple ARM instrument data streams and VAP data streams are involved in this data product. We recommend that users read the references on each observational data product and contact the relevant ARM Engineering or the ARM Translators for more information on the data limitation/uncertainties.