The long-term ARM Cloud Retrieval Ensemble Dataset (CRED) was introduced recently for all ARM permanent research sites (i.e., Southern Great Plains in Oklahoma, Tropical Western Pacific, and the North Slope of Alaska) to the climate change research community. CRED is a multi-year cloud microphysical property ensemble dataset created by assembling nine existing ground-based cloud retrievals that have been developed by different research groups. The intent of the dataset is to provide a rough estimate of the uncertainties in current retrieved cloud microphysical properties for climate model evaluation and development. The current CRED dataset contains: (1) cloud liquid effective radius, liquid water content, and liquid water path, (2) cloud ice effective radius, ice water content, and ice water path, (3) cloud liquid optical depth and ice optical depth at solar wavelength, and (4) cloud fraction and cloud total column fraction. These quantities are averaged over one-hour time intervals with a vertical resolution of 45 meters, consistent with the ARM Climate Modeling Best Estimate (CMBE) dataset, to facilitate the use of the cloud property data by climate modelers.
The creation of CRED represents an integrated effort from a focus group that consists of Atmospheric System Research scientists with expertise in cloud retrievals and ARM experts. For more details, please see the README file (login, registration required) and the technical report (report ) associated with this dataset.
Contact: Wanda Ferrell, SC-23.1, (301) 903-0043, Rickey Petty, SC-23.1, (301) 903-5548, Ashley Williamson, SC-23.1, (301) 903-3120
SC-33.1 Earth and Environmental Sciences Division, BER
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