Observational Large Ensemble
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These python datasets contain the results presented in the above paper with regard to the variability in trends over North America during DJF due to sampling of internal variability. Two types of files are available. The netcdf file contains samples from the synthetic ensemble of DJF temperatures over North America from 1966-2015. The synthetic ensemble is centered on the observed trend. Recentering the ensemble on the ensemble mean trend from the NCAR CESM1 LENS will create the Observational Large Ensemble, in which each sample can be viewed as a temperature history that could have occurred given various samplings of internal variability. The synthetic ensemble can also be recentered on any other estimate of the forced response to climate change. While the dataset is both land and ocean, it has only been validated over la' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Atmospheric science","Climate change","Climate variability","Regional trends"]} <|eot_id|>
 Here is the Description of a dataset. Description:'These python datasets contain the results presented in the above paper with regard to the variability in trends over North America during DJF due to sampling of internal variability. Two types of files are available. The netcdf file contains samples from the synthetic ensemble of DJF temperatures over North America from 1966-2015. The synthetic ensemble is centered on the observed trend. Recentering the ensemble on the ensemble mean trend from the NCAR CESM1 LENS will create the Observational Large Ensemble, in which each sample can be viewed as a temperature history that could have occurred given various samplings of internal variability. The synthetic ensemble can also be recentered on any other estimate of the forced response to climate change. While the dataset is both land and ocean, it has only been validated over la' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
These python datasets contain the results presented in the above paper with regard to the variability in trends over North America during DJF due to sampling of internal variability. Two types of files are available. The netcdf file contains samples from the synthetic ensemble of DJF temperatures over North America from 1966-2015. The synthetic ensemble is centered on the observed trend. Recentering the ensemble on the ensemble mean trend from the NCAR CESM1 LENS will create the Observational Large Ensemble, in which each sample can be viewed as a temperature history that could have occurred given various samplings of internal variability. The synthetic ensemble can also be recentered on any other estimate of the forced response to climate change. While the dataset is both land and ocean, it has only been validated over la
Atmospheric science; Climate change; Climate variability; Regional trends