Analysing Scales of Precipitation

Ordonez, Ana C.; Klingaman, Nicholas P.; Martin, Gill

doi:10.11578/dc.20211029.5

Cited by 1 publication

(3 citation statements)

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“…Analyzing Scales of Precipitation (ASoP; Klingaman et al, 2017;Martin et al, 2017;Ordonez et al, 2021) focuses on analyzing precipitation scales across space and time. In parallel, the regional climate community also has actively developed metrics packages such as the Regional Climate Model Evaluation System (RCMES; Lee et al, 2018a;Whitehall et al 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Despite the advantages, having no single best or widely accepted approach for the community to follow, does introduce complexity to the coordination of model evaluation. To facilitate collective usages of individual evaluation tools, the CMEC has initiated the development of a unified code base that technically coordinates the operation of distinct but complementary tools (Ordonez et al 2021). Currently, the PMP, ILAMB, MDTF and ASoP have become CMEC-compliant by adopting the common interface standards that define how evaluation tools interact with observational data and climate model output.…”

Section: Discussionmentioning

confidence: 99%

“…They also noted that the order of operations of regridding and calculating extremes affects the ability of models to reproduce observations. Drought metrics developed by Xue and Ullrich (2021) are not implemented in PMP directly, but are wrapped by the Coordinated Model Evaluation Capabilities (CMEC; Ordonez et al 2021), which is a parallel framework for supporting community-developed evaluation packages. Together, these metrics provide a streamlined workflow for running the entire baseline metrics via the PMP and CMEC that is ready for use by operational centers and in the CMIP7.…”

Section: Precipitationmentioning

confidence: 99%

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

Lee,

Gleckler,

Ahn

et al. 2023

Preprint

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Abstract. 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.

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