Articles | Volume 11, issue 10
https://doi.org/10.5194/gmd-11-4195-2018
https://doi.org/10.5194/gmd-11-4195-2018
Methods for assessment of models
 | 
16 Oct 2018
Methods for assessment of models |  | 16 Oct 2018

(GO)2-SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase

Katia Lamer, Ann M. Fridlind, Andrew S. Ackerman, Pavlos Kollias, Eugene E. Clothiaux, and Maxwell Kelley

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Latest update: 16 Jul 2024
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Short summary
Weather and climate predictions of cloud, rain, and snow occurrence remain uncertain, in part because guidance from observation is incomplete. We present a tool that transforms predictions into observations from ground-based remote sensors. Liquid water and ice occurrence errors associated with the transformation are below 8 %, with ~ 3 % uncertainty. This (GO)2-SIM forward-simulator tool enables better evaluation of cloud, rain, and snow occurrence predictions using available observations.