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Title: An architecture for consolidating multidimensional time-series data onto a common coordinate grid

In this paper, consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. In addition, these challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of data consolidation methods, present a framework for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.
Authors:
ORCiD logo [1] ;  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Grant/Contract Number:
AC05-76RL01830
Type:
Published Article
Journal Name:
Earth Science Informatics
Additional Journal Information:
Journal Volume: 10; Journal Issue: 2; Journal ID: ISSN 1865-0473
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; datastream; flattened arrays; data slices; data consolidation; regridding; data quality
OSTI Identifier:
1336507
Alternate Identifier(s):
OSTI ID: 1341743

Shippert, Tim, and Gaustad, Krista. An architecture for consolidating multidimensional time-series data onto a common coordinate grid. United States: N. p., Web. doi:10.1007/s12145-016-0285-z.
Shippert, Tim, & Gaustad, Krista. An architecture for consolidating multidimensional time-series data onto a common coordinate grid. United States. doi:10.1007/s12145-016-0285-z.
Shippert, Tim, and Gaustad, Krista. 2016. "An architecture for consolidating multidimensional time-series data onto a common coordinate grid". United States. doi:10.1007/s12145-016-0285-z.
@article{osti_1336507,
title = {An architecture for consolidating multidimensional time-series data onto a common coordinate grid},
author = {Shippert, Tim and Gaustad, Krista},
abstractNote = {In this paper, consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. In addition, these challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of data consolidation methods, present a framework for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.},
doi = {10.1007/s12145-016-0285-z},
journal = {Earth Science Informatics},
number = 2,
volume = 10,
place = {United States},
year = {2016},
month = {12}
}