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ORIGINAL RESEARCH article

Front. Remote Sens.
Sec. Data Fusion and Assimilation
Volume 5 - 2024 | doi: 10.3389/frsen.2024.1395442

Summarizing multiple aspects of triple collocation analysis in a single diagram

Provisionally accepted
  • 1 University of Arizona, Tucson, United States
  • 2 Goddard Institute for Space Studies (NASA), New York, New York, United States
  • 3 Langley Research Center, National Aeronautics and Space Administration, Hampton, Virginia, United States
  • 4 Analytical Mechanics Associates, Hampton, Virginia, United States

The final, formatted version of the article will be published soon.

    With our ever-growing global observation network, it is expected that we shall routinely analyze records of geophysical variables such as temperature from multiple collocated instruments.Validating datasets in this situation is not a trivial task because every observing system has its own bias and noise. Triple collocation is a general statistical framework to estimate the error characteristics in three or more observational-based datasets. In a triple colocation analysis, several metrics are routinely reported but it becomes unwieldy when the analysis gets complicated.A new formula of error variance is derived for connecting the key terms in the triple collocation theory. A diagram based on this formula is devised to facilitate triple collocation analysis of any data from observations, as illustrated using three aerosol optical depth datasets from the recent Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). An observational-based skill score is also derived to evaluate the quality of three datasets by taking into account of both error variance and correlation coefficient. Several applications are discussed and sample plotting routines are provided.

    Keywords: triple collocation, Activate, RSP, HSRL-2, Polarimeter, lidar, MODIS, aerosol

    Received: 03 Mar 2024; Accepted: 12 Jun 2024.

    Copyright: © 2024 Siu, Zeng, Sorooshian, Cairns, Ferrare, Hair, Hostetler, Painemal and Schlosser. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Leong Wai Siu, University of Arizona, Tucson, United States

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