opportunities record: dafc73b1-8c95-11ef-944e-41a8eb05f654 (v1.2)

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Category Description

These are the intended use-case/justification for one or multiple variable groups. Opportunities are linked to relevant experiment groups. Identifying opportunities helps to provide a structure to map variables against requirements. Each opportunity description will convey why this combination of variables and experiments is important and how they contribute to impact.



AttributeValue
descriptionThis set of variables consists of a number of basic variables that are needed for quantifying both how the mean climate and its variability are changing over time and for understanding the mechanisms involved. On the monthly timescale it includes fields for assessing global mean temperature, hydrological, sea level, and circulation changes in both the atmosphere and ocean as well as top of atmosphere and surface fluxes for diagnosing energy balances. Fields for understanding the role of clouds in the climate system are requested, as are fields for quantifying changes in the ocean circulation. We also request variables that would help to understand the origins of difference in co2 forcing among simulations when run in emissions driven mode and quantities that can be used to diagnose the various forcings that the climate is being influenced by in each simulation. We also suggest that zonal mean (or 3D) atmospheric temperature at high vertical resolution to allow the upper levels to be examined would be beneficial to better capture stratospheric satellite weighting functions. We also suggest daily fields that can be used to understand the time evolution of compound extremes and daily surface fluxes that can be used to understand those extremes. Daily variables that can be used to look at changes in synoptic features such as storm tracks are also requested.
expected_impactsThere are many use cases for these data. There are examples in Simpson et al (2023) 10.1175/JCLI-D-22-0666.1 where temperature, surface fluxes, and ocean circulation fields were used to diagnose the impacts of aerosol forcing on the climate system. There are numerous examples where people have used quantities that describe the aerosol amount in the atmosphere along with surface temperature to attribute the historical evolution of the climate system to different forcings e.g., https://doi.org/10.1175/JCLI-D-21-0656.1. As an example of the use of high frequency data in DAMIP simulations, the recent study of Chemke and Coumou (2024) 10.1038/s41612-024-00640-2 demonstrated that aerosol forcing in CMIP6 could explain the observed weakening of the summertime storm tracks but that this was not reproduced with CMIP5 forcings.
justification_of_resourcesMost of the variables that are proposed here are regularly used and fall under the baseline set of variables category. We consider these variables to be essential for assessing the behavior of models and understanding the role of forcings in the climate system. Given the strong overlap between these and baseline variables, I won't elaborate further her, but I'd be happy to as we are finalizing the data request.
lead_themeAtmosphere
minimum_ensemble_size1
nameDetection and Attribution
opportunity_id26

Data Request Information

data_request_themesImpacts & Adaptation, Atmosphere, Land & Land-Ice, Ocean & Sea-Ice, Earth System
experiment_groupsdamip_experiment_group
mipsDAMIP, PMIP, FireMIP, DCPP, TIPMIP, DAMIP
time_subsets80ac3156-a698-11ef-914a-613c0433d878
variable_groupsocean_grid_low_priority, DAMIP_daily, DAMIP_monthly, ocean_grid

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