Vom 20.12.2025 bis 11.01.2026 ist die Universitätsbibliothek geschlossen. Ab dem 12.01.2026 gelten wieder die regulären Öffnungszeiten. Ausnahme: Medizinische Hauptbibliothek und Zentralbibliothek sind bereits ab 05.01.2026 wieder geöffnet. Weitere Informationen

Treffer: Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3.

Title:
Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3.
Source:
EGUsphere; 11/24/2023, p1-48, 48p
Database:
Complementary Index

Weitere Informationen

Systematic, routine, and comprehensive evaluation of Earth System Models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The PCMDI Metrics Package (PMP) is an open-source Python software package that provides 'quick-look' objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as El Niño-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including extremes. The PMP results are produced in the context of all model simulations contributed to CMIP6 and earlier CMIP phases. An important priority of the PMP is to document evaluation statistics for all Historical and AMIP simulations submitted to recent phases of CMIP, providing version-controlled information for all data sets and software packages being used. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. In this paper, we present an overview of the PMP including its history to date, capabilities, recent updates, and future direction. [ABSTRACT FROM AUTHOR]

Copyright of EGUsphere is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)