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The mapping of irregular observations to three dimensional data is
accomplished using Objective Analysis techniques. Objective Analysis
utilizes the Gauss-Markov or minimum error variance criterion to map the
available data onto horizontal grids. The process repeats for different
vertical levels and analysis times. HOPS includes two flavors of Objective
Analysis: the full-matrix (global) Objective Analysis (OAG) and a local
approximation (OA). Both OA's are actually 2-level OA's producing first
a slowly varying "mean" field from synoptic data and/or
climatology. A 2^{nd} level OA maps the synoptic data onto this
mean field.

The local objective analysis program uses a local approximation to the full correlation matrix. In particular, it allows the user to limit the contributions to a pre-specified number of the most strongly correlate points. (Historically, this package was developed after a student "burned up" an entire year's allocation on a supercomputer for one analysis.) This approximation gives the local OA an advantage in speed, but tends to produce noisier output.

The global objective analysis program inverts the entire correlation
matrix. This produces naturally smooth fields at a cost of time and
the memory requirements of the program. In the cases where these costs
are acceptable, the global OA is *highly* recommended over the local
OA.

Directory |
Files |
Date(MM/DD/YYYY) |
Size Compressed(bytes) |
Size Uncompressed(bytes) |

OA/ |
Readme.oa | 01/23/2001 | 21733 | |

oa_6.6.tar.Z | 01/23/2001 | 139905 | 552960 | |

Ex_oa_6.6.tar.gz | 01/23/2001 | 4866091 | 7809024 | |

OAG/ |
Readme.oag | 01/23/2001 | 21315 | |

oag_5.6.tar.Z | 01/23/2001 | 135854 | 534528 | |

Ex_oag_5.6.tar.gz | 01/23/2001 | 4874217 | 7821312 |