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Towards improved and more routine Earth system model evaluation in CMIP

Journal Article · · Earth System Dynamics (Online)
 [1];  [2];  [3];  [4];  [2];  [5];  [6];  [7];  [8];  [9];  [10];  [1];  [2]
  1. German Aerospace Center (DLR), Oberpfaffenhofen (Germany). Inst. for Atmospheric Physics
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison (PCMDI)
  3. Univ. of Bergen (Norway). Geophysical Inst., Bjerknes Centre for Climate Research; Uni Research Climate, Bergen (Norway)
  4. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States). Geophysical Fluid Dynamics Lab.
  5. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States). Geophysical Fluid Dynamics Lab.; Princeton Univ., NJ (United States). Cooperative Inst. for Climate Science
  6. French National Center for Scientific Research (CNRS), Paris (France). Pierre Simon Laplace Inst.; Univ. of Reading (United Kingdom). National Centre for Atmospheric Science
  7. French National Center for Scientific Research (CNRS), Saclay (France). Pierre Simon Laplace Inst.
  8. German Climate Computing Center, Hamburg (Germany)
  9. Univ. of Reading (United Kingdom). National Centre for Atmospheric Science; STFC Rutherford Appleton Lab., Didcot (United Kingdom). Centre for Environmental Data Analysis
  10. National Center for Atmospheric Research, Boulder, CO (United States)

The Coupled Model Intercomparison Project (CMIP) has successfully provided the climate community with a rich collection of simulation output from Earth system models (ESMs) that can be used to understand past climate changes and make projections and uncertainty estimates of the future. Confidence in ESMs can be gained because the models are based on physical principles and reproduce many important aspects of observed climate. More research is required to identify the processes that are most responsible for systematic biases and the magnitude and uncertainty of future projections so that more relevant performance tests can be developed. At the same time, there are many aspects of ESM evaluation that are well established and considered an essential part of systematic evaluation but have been implemented ad hoc with little community coordination. Given the diversity and complexity of ESM analysis, we argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently and consistently. We provide a perspective and viewpoint on how a more systematic, open, and rapid performance assessment of the large and diverse number of models that will participate in current and future phases of CMIP can be achieved, and announce our intention to implement such a system for CMIP6. Accomplishing this could also free up valuable resources as many scientists are frequently "re-inventing the wheel" by re-writing analysis routines for well-established analysis methods. A more systematic approach for the community would be to develop and apply evaluation tools that are based on the latest scientific knowledge and observational reference, are well suited for routine use, and provide a wide range of diagnostics and performance metrics that comprehensively characterize model behaviour as soon as the output is published to the Earth System Grid Federation (ESGF). The CMIP infrastructure enforces data standards and conventions for model output and documentation accessible via the ESGF, additionally publishing observations (obs4MIPs) and reanalyses (ana4MIPs) for model intercomparison projects using the same data structure and organization as the ESM output. This largely facilitates routine evaluation of the ESMs, but to be able to process the data automatically alongside the ESGF, the infrastructure needs to be extended with processing capabilities at the ESGF data nodes where the evaluation tools can be executed on a routine basis. Efforts are already underway to develop community-based evaluation tools, and we encourage experts to provide additional diagnostic codes that would enhance this capability for CMIP. And, at the same time, we encourage the community to contribute observations and reanalyses for model evaluation to the obs4MIPs and ana4MIPs archives. The intention is to produce through the ESGF a widely accepted quasi-operational evaluation framework for CMIP6 that would routinely execute a series of standardized evaluation tasks. Over time, as this capability matures, we expect to produce an increasingly systematic characterization of models which, compared with early phases of CMIP, will more quickly and openly identify the strengths and weaknesses of the simulations. This will also reveal whether long-standing model errors remain evident in newer models and will assist modelling groups in improving their models. Finally, this framework will be designed to readily incorporate updates, including new observations and additional diagnostics and metrics as they become available from the research community.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Grant/Contract Number:
AC52-07NA27344; FC02-97ER62402
OSTI ID:
1395317
Journal Information:
Earth System Dynamics (Online), Journal Name: Earth System Dynamics (Online) Journal Issue: 4 Vol. 7; ISSN 2190-4987
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (20)

Benchmarking CMIP5 models with a subset of ESA CCI Phase 2 data using the ESMValTool journal December 2017
Quantifying climate feedbacks in polar regions journal May 2018
Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP text January 2020
Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions journal February 2020
Probabilistic evaluation of competing climate models journal October 2017
ESD Reviews: Climate feedbacks in the Earth system and prospects for their evaluation journal January 2019
AerChemMIP: quantifying the effects of chemistry and aerosols in CMIP6 journal January 2017
An interactive ocean surface albedo scheme (OSAv1.0): formulation and evaluation in ARPEGE-Climat (V6.1) and LMDZ (V5A) journal January 2018
Requirements for a global data infrastructure in support of CMIP6 journal January 2018
The use of the Community Earth System Model in human dimensions climate research and applications journal January 2019
Quantifying the agreement between observed and simulated extratropical modes of interannual variability journal July 2018
Evaluation of Impact of Potential Extreme Rainfall Events on Mining in Peru journal July 2018
Constraining Climate Model Projections of Regional Precipitation Change journal September 2019
Taking climate model evaluation to the next level journal January 2019
Deep learning and process understanding for data-driven Earth system science journal February 2019
Taking climate model evaluation to the next level text January 2019
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Multivariable integrated evaluation of model performance with the vector field evaluation diagram journal January 2017
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