dataset

Metadata for 'Initialization and ensemble generation for decadal climate prediction system MiKlip'

General Information

Name
Initialization and ensemble generation for decadal climate prediction system MiKlip
Summary
Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system "Mittelfristige Klimaprognose" (MiKlip). Among the tested methods, three tackle aspects of model-consistent initialization using the ensemble Kalman filter (EnKF), the filtered anomaly initialization (FAI) and the initialization method by partially coupled spin-up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter (EDF) corrects each ensemble member with the ensemble mean during model integration. And the bred vectors (BV) perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low-resolution configuration (Preop-LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization.
Location(s)
World: Longitude 0 to 360 Latitude -90 to 90
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0)
Access constraints
registered users
Size
84.86 GiB (91119534948 Byte)
Format
tar-File(s)
Progress
completely archived
Creation Date
Future Review Date
2028-09-18
Download Permission
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Citation

Citation
Polkova, Iuliia (2018). Initialization and ensemble generation for decadal climate prediction system MiKlip. World Data Center for Climate (WDCC) at DKRZ. http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=DKRZ_LTA_122_ds00001

 
[Entry acronym: DKRZ_LTA_122_ds00001] [Entry id: 3758132]