Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles

Abstract. Comparisons with ground-based correlative measurements constitute a key component in the validation of satellite data on atmospheric composition. The error budget of these comparisons contains not only the measurement errors but also several terms related to differences in sampling and smoothing of the inhomogeneous and variable atmospheric field. A versatile system for Observing System Simulation Experiments (OSSEs), named OSSSMOSE, is used here to quantify these terms. Based on the application of pragmatic observation operators onto high-resolution atmospheric fields, it allows a simulation of each individual measurement, and consequently, also of the differences to be expected from spatial and temporal field variations between both measurements making up a comparison pair. As a topical case study, the system is used to evaluate the error budget of total ozone column (TOC) comparisons between GOME-type direct fitting (GODFITv3) satellite retrievals from GOME/ERS2, SCIAMACHY/Envisat, and GOME-2/MetOp-A, and ground-based direct-sun and zenith-sky reference measurements such as those from Dobsons, Brewers, and zenith-scattered light (ZSL-)DOAS instruments, respectively. In particular, the focus is placed on the GODFITv3 reprocessed GOME-2A data record vs. the ground-based instruments contributing to the Network for the Detection of Atmospheric Composition Change (NDACC). The simulations are found to reproduce the actual measurements almost to within the measurement uncertainties, confirming that the OSSE approach and its technical implementation are appropriate. This work reveals that many features of the comparison spread and median difference can be understood as due to metrological differences, even when using strict colocation criteria. In particular, sampling difference errors exceed measurement uncertainties regularly at most mid-and high-latitude stations, with values up to 10 % and more in extreme cases. Smoothing difference errors only play a role in the comparisons with ZSL-DOAS instruments at high latitudes, especially in the presence of a polar vortex due to the strong TOC gradient it induces. At tropical latitudes, where TOC variability is lower, both types of errors remain below about 1 % and consequently do not contribute significantly to the comparison error budget. The detailed analysis of the comparison results, including the metrological errors, suggests that the published random measurement uncertainties for GODFITv3 reprocessed satellite data are potentially overestimated, and adjustments are proposed here. This successful application of the OSSSMOSE system to close for the first time the error budget of TOC comparisons, bodes well for potential future applications, which are briefly touched upon.

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“…Fassò et al, 2014), or based on some level of parametrization of atmospheric variability (e.g. Sofieva et al, 2014, and references therein).…”

Section: An Observing System Simulation Experimentsmentioning

confidence: 99%

Metrology of ground-based satellite validation: co-location mismatch and smoothing issues of total ozone comparisons

et al. 2015

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“…Both quantities were calculated to quantify uncertainty and redundancy in the IWV time series, as well as in the times series of the vertical profile of water vapour mixing ratio. In this investigation of time series of atmospheric water vapour measurements, entropy includes all contributions affecting the uncertainty of a measurements time series -sampling uncertainty, uncertainty due to the time and vertical average, atmospheric variability, and all other relevant environmental factors (Kitchen, 1989;Fassò et al, 2014), such as solar radiation affecting daytime in situ soundings. Figure 2 (left) is an example of a series of samples of the IWV for the Lindenberg instruments (Table 1), while Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Linear correlation (Pearson's or Spearman's) has typically been used to study redundant measurements and their reliability. More recently, Fassò et al (2014) presented a new approach for an advanced statistical modelling based on functional data analysis of the relationships among collocation uncertainty and a set of environmental factors (e.g. wind speed and wind direction).…”

Section: F Madonna Et Al: Quantifying the Value Of Redundant Measurmentioning

confidence: 99%

Quantifying the value of redundant measurements at GCOS Reference Upper-Air Network sites

et al. 2014

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Abstract. The potential for measurement redundancy to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. We evaluated the usefulness of entropy and mutual correlation concepts, as defined in information theory, for quantifying random uncertainty and redundancy in time series of the integrated water vapour (IWV) and water vapour mixing ratio profiles provided by five highly instrumented GRUAN (GCOS, Global Climate Observing System, Reference Upper-Air Network) stations in -2012 show that the random uncertainties on the IWV measured with radiosondes, global positioning system, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8 %. Comparisons of time series of IWV content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy with the IWV time series measured by radiosondes and therefore the highest potential to reduce the random uncertainty of the radiosondes time series. Moreover, the random uncertainty of a time series from one instrument can be reduced by ∼ 60 % by constraining the measurements with those from another instrument. The best reduction of random uncertainty is achieved by conditioning Raman lidar measurements with microwave radiometer measurements. Specific instruments are recommended for atmospheric water vapour measurements at GRUAN sites. This approach can be applied to the study of redundant measurements for other climate variables.

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“…Drift distances are generally larger in midlatitudes than in the tropics, are larger in winter than in summer, and vary with wind direction (Seidel et al 2011b). Fassò et al (2014) established a rigorous statistical basis for understanding the extent to which collocation uncertainty is related to environmental factors, altitude, and distance. Using simultaneous radiosonde profiles of pressure, temperature, humidity, and wind at two locations ~52 km apart, they showed that the largest contribution to the collocation uncertainty is related to airmass origin, affecting the direction in which the radiosonde moves.…”

Section: How Does Science Inform Gruan Operations and Plans?mentioning

confidence: 99%

“…Similarly, the collocation information arising from this comparison provides a valuable piece of metadata to GRUAN profiles and allows for comparisons between stations across GRUAN for each satellite. Currently, the analysis contains no specified uncertainty on the satellite measurements and also no consideration of collocation uncertainty (Fassò et al 2014). Collocation experiments based on GRUAN profiles, satellite soundings, and GNSSbased radio occultations are expected to provide further insight (WMO 2014a).…”

Section: What Observational Data Products and Services Is Gruan Provimentioning

confidence: 99%

Reference Upper-Air Observations for Climate: From Concept to Reality

Bodeker

Bojinski

Cimini

et al. 2016

Bulletin of the American Meteorological Society

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The three main objectives of the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) are to provide long-term high-quality climate records of vertical profiles of selected essential climate variables (ECVs), to constrain and calibrate data from more spatially comprehensive global networks, and to provide measurements for process studies that permit an in-depth understanding of the properties of the atmospheric column. In the five years since the first GRUAN implementation and coordination meeting and the printing of an article (Seidel et al.) in this publication, GRUAN has matured to become a functioning network that provides reference-quality observations to a community of users. This article describes the achievements within GRUAN over the past five years toward making reference-quality observations of upper-air ECVs. Milestones in the evolution of GRUAN are emphasized, including development of rigorous criteria for site certification and assessment, the formal certification of the first GRUAN sites, salient aspects of the GRUAN manual and guide to operations, public availability of GRUAN’s first data product, outcomes of a network expansion workshop, and key results of scientific studies designed to provide a sound scientific foundation for GRUAN operations. Two defining attributes of GRUAN are 1) that every measurement is accompanied by a traceable estimate of the measurement uncertainty and 2) that data quality and continuity are maximized because network changes are minimized and managed. This article summarizes how these imperatives are being achieved for existing and planned data products and provides an outlook for the future, including expected new data streams, network expansion, and critical needs for the ongoing success of GRUAN.

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Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles

Cited by 31 publications

References 26 publications

Metrology of ground-based satellite validation: co-location mismatch and smoothing issues of total ozone comparisons

Metrology of ground-based satellite validation: co-location mismatch and smoothing issues of total ozone comparisons

Quantifying the value of redundant measurements at GCOS Reference Upper-Air Network sites

Reference Upper-Air Observations for Climate: From Concept to Reality

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