Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

Abstract

Abstract. There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA-CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is "correct". Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA-CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA-CLIM project. However, the approach laid out should be more widely applicable across a broad range of application areas. If broadly adopted, the system-of-systems approach will have potential benefits in guiding users to the most appropriate set of observations for their needs and in highlighting to network owners and operators areas for potential improvement.

Observing Requirements for Long-Term Climate Records at the Ocean Surface

“…OceanSITES provides the most consistent source of surface marine data presently available with unified access and common data formats. Whilst it does not strictly conform to the definition of a reference network used for observations over land (Thorne et al, 2017b) the maintenance of a high quality array of moored observations is critical for the maintenance of long-term records. The number of OceanSITES currently providing most of the ECVs in the scope of this paper is about 20, but an extension of similar size has been recommended in support of air-sea fluxes (Cronin et al, 2019), sampling regions thought to be particularly important for understanding the mechanisms of air-sea interaction and providing validation observations for satellites.…”

Towards a global land surface climate fiducial reference measurements network

“…Our proposal is that a surface climate fiducial reference measurement network will enhance the value of existing observing networks. To see how this would work it is helpful to envisage global measurements as consisting of three tiers (Figure ) (Thorne et al , ): fiducial reference measurement networks; baseline networks; and comprehensive networks.…”

Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals

“…MWR adds value to GRUAN by providing redundant measurements with respect to radiosondes, but covering the complete diurnal cycle at high (e.g., 1 min) temporal resolution. The various sources of uncertainty for MWR retrievals have been reviewed in the framework of the GRUAN-related GAIA-CLIM project (http://gaia-clim.eu/, last access: 1 May 2018, Thorne et al, 2017). One such source is the spectroscopic parameter uncertainty, which appears to be the least investigated among all (Maschwitz et al, 2013; GAIA-CLIM, Gaps Assessment and Impacts Document (GAID) -G2.37, 2017).…”