|Earth System Model Evaluation Tool (ESMValTool) v2.0-diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP
|Tipo di pubblicazione
|Articolo su Rivista peer-reviewed
|Anno di Pubblicazione
|Weigel, K., Bock L., Gier B.K., Lauer A., Righi M., Schlund M., Adeniyi K., Andela B., Arnone E., Berg P., Caron L.-P., Cionni Irene, Corti S., Drost N., Hunter A., Lledó L., Mohr C.W., Paçal A., Pérez-Zanón N., Predoi V., Sandstad M., Sillmann J., Sterl A., Vegas-Regidor J., Von Hardenberg J., and Eyring V.
|Geoscientific Model Development
|Climate change, climate effect, climate modeling, detection method, extreme event, Regional climate
This paper complements a series of now four publications that document the release of the Earth System Model Evaluation Tool (ESMValTool) v2.0. It describes new diagnostics on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) which are participating in the Coupled Model Intercomparison Project (CMIP). The second release of this tool aims to support the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). Furthermore, datasets from other models and observations can be analysed. The diagnostics for the hydrological cycle include several precipitation and drought indices, as well as hydroclimatic intensity and indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). The latter are also used for identification of extreme events, for impact assessment, and to project and characterize the risks and impacts of climate change for natural and socio-economic systems. Further impact assessment diagnostics are included to compute daily temperature ranges and capacity factors for wind and solar energy generation. Regional scales can be analysed with new diagnostics implemented for selected regions and stochastic downscaling. ESMValTool v2.0 also includes diagnostics to analyse large multi-model ensembles including grouping and selecting ensemble members by user-specified criteria. Here, we present examples for their capabilities based on the well-established CMIP Phase 5 (CMIP5) dataset. © 2021 Katja Weigel et al.
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