Data mining ocean model output at the Naval Oceanographic Office Shared Resource Center

2004 ◽  
Author(s):  
P. Gruzinskas ◽  
A. Haas ◽  
L. Goon
Keyword(s):  
Data Mining ◽  
Ocean Model ◽  
Model Output ◽  
Shared Resource ◽  
Resource Center

scholarly journals Detection of Fronts as a Metric for Numerical Model Accuracy

2019 ◽  
Vol 36 (8) ◽  
pp. 1547-1561
Author(s):  
Elizabeth M. Douglass ◽  
Andrea C. Mask
Keyword(s):  
Numerical Model ◽  
Region Of Interest ◽  
Ocean Model ◽  
Minimum Size ◽  
Model Output ◽  
Oceanic Fronts ◽  
Hybrid Coordinate Ocean Model ◽  
Quantitative Metrics ◽  
Coastal Ocean Model ◽  
Along Track

AbstractAs numerical modeling advances, quantitative metrics are necessary to determine whether the model output accurately represents the observed ocean. Here, a metric is developed based on whether a model places oceanic fronts in the proper location. Fronts are observed and assessed directly from along-track satellite altimetry. Numerical model output is then interpolated to the locations of the along-track data, and fronts are detected in the model output. Scores are determined from the percentage of observed fronts correctly simulated in the model and from the percentage of modeled fronts confirmed by observations. These scores depend on certain parameters such as the minimum size of a front, which will be shown to be geographically dependent. An analysis of two models, the Hybrid Coordinate Ocean Model (HYCOM) and the Navy Coastal Ocean Model (NCOM), is presented as an example of how this metric might be applied and interpreted. In this example, scores are found to be relatively stable in time, but strongly dependent on the mesoscale variability in the region of interest. In all cases, the metric indicates that there are more observed fronts not found in the models than there are modeled fronts missing from observations. In addition to the score itself, the analysis demonstrates that modeled fronts have smaller amplitude and are less steep than observed fronts.

Cloud archiving and data mining of High-Resolution Rapid Refresh forecast model output

2017 ◽  
Vol 109 ◽  
pp. 43-50 ◽  
Author(s):  
Brian K. Blaylock ◽  
John D. Horel ◽  
Samuel T. Liston
Keyword(s):  
Data Mining ◽  
High Resolution ◽  
Forecast Model ◽  
Model Output

Transport matrices from standard ocean-model output and quantifying circulation response to climate change

2019 ◽  
Vol 135 ◽  
pp. 1-13 ◽  
Author(s):  
Matthew A. Chamberlain ◽  
Richard J. Matear ◽  
Mark Holzer ◽  
Daohua Bi ◽  
Simon J. Marsland
Keyword(s):  
Climate Change ◽  
Ocean Model ◽  
Model Output

scholarly journals Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms

2007 ◽  
Vol 22 (5) ◽  
pp. 1123-1131 ◽  
Author(s):  
Richard L. Bankert ◽  
Michael Hadjimichael
Keyword(s):  
Data Mining ◽  
Weather Prediction ◽  
Ground Truth ◽  
Cloud Base ◽  
Model Output ◽  
Model Data ◽  
Single Station ◽  
Low Cloud ◽  
Nwp Model ◽  
Model Output Statistics

Abstract Accurate cloud-ceiling-height forecasts derived from numerical weather prediction (NWP) model data are useful for aviation and other interests where low cloud ceilings have an impact on operations. A demonstration of the usefulness of data-mining methods in developing cloud-ceiling forecast algorithms from NWP model output is provided here. Rapid Update Cycle (RUC) 1-h forecast data were made available for nearly every hour in 2004. Various model variables were extracted from these data and stored in a database of hourly records for routine aviation weather report (METAR) station KJFK at John F. Kennedy International Airport along with other single-station locations. Using KJFK cloud-ceiling observations as ground truth, algorithms were derived for 1-, 3-, 6-, and 12-h forecasts through a data-mining process. Performance of these cloud-ceiling forecast algorithms, as evaluated through cross-validation testing, is compared with persistence and Global Forecast System (GFS) model output statistics (MOS) performance (6 and 12 h only) over the entire year. The 1-h algorithms were also compared with the RUC model cloud-ceiling (or cloud base) height translation algorithms. The cloud-ceiling algorithms developed through data mining outperformed these RUC model translation algorithms, showed slightly better skill and accuracy than persistence at 3 h, and outperformed persistence at 6 and 12 h. Comparisons to GFS MOS (which uses observations in addition to model data for algorithm derivation) at 6 h demonstrated similar performance between the two methods with the cloud-ceiling algorithm derived through data mining demonstrating more skill at 12 h.

scholarly journals Annular Modes in a Multiple Migrating Zonal Jet Regime

2007 ◽  
Vol 64 (11) ◽  
pp. 4053-4068 ◽  
Author(s):  
Cegeon J. Chan ◽  
R. Alan Plumb ◽  
Ivana Cerovecki
Keyword(s):  
Ocean Model ◽  
Heat Fluxes ◽  
Residual Flow ◽  
Model Output ◽  
Residual Circulation ◽  
Annular Modes ◽  
Zonal Jets ◽  
Momentum Fluxes ◽  
Leading Mode ◽  
Baroclinic Zone

Abstract The authors investigate the dynamics of zonal jets in a semihemisphere zonally reentrant ocean model. The forcings imposed in the model are an idealized atmospheric wind stress and relaxation to a latitudinal temperature profile held constant in time. While there are striking similarities to the observed atmospheric annular modes, where the leading mode of variability is associated with the primary zonal jet’s meridional undulation, secondary (weaker) jets emerge and systematically migrate equatorward. The model output suggests the following mechanism for the equatorward migration: while the eddy momentum fluxes sustain the jets, the eddy heat fluxes have a poleward bias causing an anomalous residual circulation with poleward (equatorward) flow on the poleward (equatorward) flanks. By conservation of mass, there must be a rising residual flow at the jet. From the thermodynamics equation, the greatest cooling occurs at the jet core, thus creating a tendency to reduce the baroclinicity on the poleward flank, while enhancing it on the equatorward flank. Consequently, the baroclinic zone shifts, perpetuating the jet migration.

scholarly journals Tracking the long-distance dispersal of marine organisms: sensitivity to ocean model resolution

2013 ◽  
Vol 10 (81) ◽  
pp. 20120979 ◽  
Author(s):  
Nathan F. Putman ◽  
Ruoying He
Keyword(s):  
Ocean Circulation ◽  
Circulation Model ◽  
Ocean Model ◽  
Marine Organisms ◽  
Model Output ◽  
Ocean Circulation Model ◽  
Time Step ◽  
Long Distance ◽  
Near Surface ◽  
Basin Scale

Ocean circulation models are widely used to simulate organism transport in the open sea, where challenges of directly tracking organisms across vast spatial and temporal scales are daunting. Many recent studies tout the use of ‘high-resolution’ models, which are forced with atmospheric data on the scale of several hours and integrated with a time step of several minutes or seconds. However, in many cases, the model's outputs that are used to simulate organism movement have been averaged to considerably coarser resolutions (e.g. monthly mean velocity fields). To examine the sensitivity of tracking results to ocean circulation model output resolution, we took the native model output of one of the most sophisticated ocean circulation models available, the Global Hybrid Coordinate Ocean Model, and averaged it to commonly implemented spatial and temporal resolutions in studies of basin-scale dispersal. Comparisons between simulated particle trajectories and in situ near-surface drifter trajectories indicated that ‘over averaging’ model output yields predictions inconsistent with observations. Further analyses focused on the dispersal of juvenile sea turtles indicate that very different inferences regarding the pelagic ecology of these animals are obtained depending on the resolution of model output. We conclude that physical processes occurring at the scale of days and tens of kilometres should be preserved in ocean circulation model output to realistically depict the movement marine organisms and the resulting ecological and evolutionary processes.

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