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Gridding Data in HOPS

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 2nd level OA maps the synoptic data onto this mean field.

Objective Analysis in Action
April 1999 Data April Climatology Gridded Surface Temperature


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.

Local vs Global OA
Local Objective Analysis Global Objective Analysis

Objective Analysis Software

Directory Files Date
Size Compressed
Size Uncompressed
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