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Title: A Data Set for Intercomparing the Transient Behavior of Dynamical Model-Based Subseasonal to Decadal Climate Predictions

Journal Article · · Journal of Advances in Modeling Earth Systems
ORCiD logo [1];  [2]; ORCiD logo [3];  [2];  [4];  [5];  [6]; ORCiD logo [7];  [8]
  1. Univ. de Buenos Aires (Argentina); Inst. Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires (Argentina)
  2. Environment and Climate Change Canada, British Columbia (Canada)
  3. Russian Academy of Sciences, Moscow (Russia); Hydrometcentre of Russia, Moscow (Russia); Moscow Inst. of Physics and Technology, Dolgoprudny (Russia)
  4. Barcelona Supercomputing Center (BSC) (Spain); Inst. Catalana de Recerca i Estudis Avançats (ICREA), Barcelona (Spain)
  5. Univ. de Barcelona (UB) (Spain)
  6. Univ. Catholique de Louvain, Louvain‐la‐Neuve (Belgium)
  7. National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
  8. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
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Climate predictions using coupled models in different time scales, from intraseasonal to decadal, are usually affected by initial shocks, drifts, and biases, which reduce the prediction skill. These arise from inconsistencies between different components of the coupled models and from the tendency of the model state to evolve from the prescribed initial conditions toward its own climatology over the course of the prediction. Aiming to provide tools and further insight into the mechanisms responsible for initial shocks, drifts, and biases, this paper presents a novel data set developed within the Long Range Forecast Transient Intercomparison Project, LRFTIP. This data set has been constructed by averaging hindcasts over available prediction years and ensemble members to form a hindcast climatology, that is a function of spatial variables and lead time, and thus results in a useful tool for characterizing and assessing the evolution of errors as well as the physical mechanisms responsible for them. A discussion on such errors at the different time scales is provided along with plausible ways forward in the field of climate predictions

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
89243018SSC000007; AC05-76RL01830
OSTI ID:
1828865
Report Number(s):
PNNL-SA--166611
Journal Information:
Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Journal Issue: 9 Vol. 13; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English

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54 ENVIRONMENTAL SCIENCES