Knowledge graph centered on Three-phase meteorological QA/QC workflow with 72 nodes and 163 connections. Top connected: groundwater storage dynamics, leaf water content, air temperature, carbon cycling, precipitation.
A comprehensive statistical framework for quality assurance and quality control of meteorological time series data involving preliminary data exploration, quality assessment with outlier detection, and quality control with missing value imputation.
Synthesized from method descriptions across 2 papers using this protocol.
Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data (2021), Stochastic environmental research and risk assessment. The protocol was originally introduced by Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado (2019), IEEE Access. Implementations in other papers (listed below) may differ.