.png){kind=icon}
.png){kind=icon}
Return
Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices
.png){kind=icon}
PRE
AI
S
B
E
B
B
D
F
J
J
J
E
B
S
J
B
D
DOI：10.1175/BAMS-D-25-0079.1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Climate model simulations are an important source of information about our planet's climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space-time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation. Significance Statement: Computer models that simulate Earth system, known as climate models, are important tools for understanding how climate processes work and provide estimates of the climate system in the past and the future. Policy decisions regarding how to adapt to and limit the impact of climate change rely on these models, and it is, therefore, important to know how well they capture the real world. Real-world observations play an important role in understanding how well climate models represent Earth's climate system. We describe various aspects of using observations for model evaluation and suggest best practices to make this process more efficient, accurate, and inclusive of a wider number of observed phenomena. Considerations and best practices are presented for the use of observations in climate model evaluation. The discussion centers on practices to support next-generation evaluation for Coupled Model Intercomparison Project simulations.
Keywords:
Climate records
Satellite observations
Surface observations
Climate models
Diagnostics
Model evaluation/ performance
Journal
IF:
5.9
Papers:
3.7K
Citations:
2.7W
Organization
Cited Papers