Designing the Social Context for Easier Verification, Validation, and Uncertainty Quantification of Earth Science Data
Abstract
Verification, Validation, and Uncertainty Quantification (VVUQ) are key actions that support conclusions based on Earth science data. Communities of data producers and users must undertake VVUQ when they create and use their data. The strategies [S] and tools [T] suggested below come from successful use on two large NASA projects. The first was the Earth Radiation Budget Experiment (ERBE). The second is the investigation of Clouds and the Earth's Radiant Energy System (CERES). [S] 1. Partition the production system into subsystems that deal with data transformations confined to limited space and time scales. Simplify the subsystems to minimize the number of data transformations in each subsystem. [S] 2. Derive algorithms from the fundamental physics and chemistry governing the parameters in each subsystem including those for instrument calibration. [S] 3. Use preliminary uncertainty estimates to detect unexpected discrepancies. Removing these requires diagnostic work as well as development and testing of fixes. [S] 4. Make sure there are adequate resources to support multiple end-to-end reprocessing of all data products. [T] 1. Create file identifiers that accommodate temporal and spatial sequences of data files and subsystem version changes. [T] 2. Create libraries of parameters used in common by different subsystems to reduce errors due to inconsistent values. [T] 3. Maintain a list of action items to record progress on resolving discrepancies. [T] 4. Plan on VVUQ activities that use independent data sources and peer review before distributing and archiving data. The goal of VVUQ is to provide a transparent link between the data and the physics and chemistry governing the measured quantities. The VVUQ effort also involves specialized domain experience and nomenclature. It often requires as much effort as the original system development. ERBE and CERES demonstrated that these strategies and tools can reduce the cost of VVUQ for Earth science data products.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMNG31A0158B
- Keywords:
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- 3315 Data assimilation;
- ATMOSPHERIC PROCESSES;
- 1910 Data assimilation;
- integration and fusion;
- INFORMATICS;
- 1990 Uncertainty;
- INFORMATICS;
- 3260 Inverse theory;
- MATHEMATICAL GEOPHYSICS