Modelling collocation uncertainty of 3D atmospheric profiles

Ignaccolo, Rosaria; Franco‐Villoria, Maria; Fassò, Alessandro

doi:10.1007/s00477-014-0890-7

Cited by 17 publications

(16 citation statements)

References 34 publications

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“…between 1000 and 500 hPa over the Arctic cap, a natural choice is to use data in the form of atmospheric profiles. In this case, the appropriate statistical modeling technique may be based on a functional data approach (see, e.g., Fassò et al 2014;Ignaccolo et al 2015). Now, u is given by the integral over a volume, but its optimal estimatorû may be expressed again as linear function u 5 Ay where now matrix A depends on the functional spatial covariance and is given by the integrated functional kriging estimator.…”

Section: Spatial Averagesmentioning

confidence: 99%

Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment

Bodeker

Fassò

Chang

et al. 2017

Journal of Applied Meteorology and Climatology

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Observing systems consisting of a finite number of in situ monitoring stations can provide high-quality measurements with the ability to quality assure both the instruments and the data but offer limited information over larger geographic areas. This paper quantifies the spatial coverage represented by a finite set of monitoring stations by using global data-data that are possibly of lower resolution and quality. For illustration purposes, merged satellite temperature data from Microwave Sounding Units are used to estimate the representativeness of the Global Climate Observing System Reference Upper-Air Network (GRUAN). While many metrics exist for evaluating the representativeness of a site, the ability to have highly accurate monthly averaged data is essential for both trend detection and climatology evaluation. The calculated correlations of the monthly averaged upper-troposphere satellite-derived temperatures over the GRUAN stations with all other pixels around the globe show that the current 9 certified GRUAN stations have moderate correlations (r $ 0.7) for approximately 10% of the earth, but an expanded network incorporating another 15 stations would result in moderate correlations for just over 60% of the earth. This analysis indicates that the value of additional stations can be quantified by using historical, satellite, or model data and can be used to reveal critical gaps in current monitoring capabilities. Evaluating the value of potential additional stations and prioritizing their initiation can optimize networks. The expansion of networks can be evaluated in a manner that allows for optimal benefit on the basis of optimization theory and economic analyses.

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Section: Spatial Averagesmentioning

confidence: 99%

Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment

Bodeker

Fassò

Chang

et al. 2017

Journal of Applied Meteorology and Climatology

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“…In the context of the EU FP7 Monitoring Atmospheric Composition and Climate Interim Implementation (MACC-II, Inness et al, 2013), the Integrated Forecast System (IFS) at European Centre for Medium-Range Weather Forecast (ECMWF) was coupled with the Model for OZone And Related chemical Tracers (MOZART-3) transport model to include chemically reactive gases . IFS is run at T255 spectral truncation, corresponding to roughly 80 km horizontal resolution, but MOZART-3 resolution is slightly lower at 1.125…”

Section: Macc (Ifs-mozart)mentioning

confidence: 99%

“…Ridolfi et al, 2007;Lambert et al, 2012;Ignaccolo et al, 2015) and for ozone profiles (Sparling et al, 2006;Cortesi et al, 2007), they remain to be quantified for total ozone column (TOC) comparisons. This is the objective of the current paper.…”

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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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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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“…For overviews on FDA methods, see Ramsay and Silverman (2005), Ferraty and Vieu (2006), Horváth and Kokoszka (2012) or Cuevas (2014). For environmental statistical problems tackled using FDA techniques, see for example Ignaccolo et al (2015), Menafoglio et al (2014) and Ruiz-Medina and Espejo (2012).…”

Section: Introductionmentioning

confidence: 99%

Functional outlier detection by a local depth with application to NO x levels

Sguera

Galeano

Lillo

2015

Stoch Environ Res Risk Assess

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This paper proposes methods to detect outliers in functional data sets and the task of identifying atypical curves is carried out using the recently proposed kernelized functional spatial depth (KFSD). KFSD is a local depth that can be used to order the curves of a sample from the most to the least central, and since outliers are usually among the least central curves, we present a probabilistic result which allows to select a threshold value for KFSD such that curves with depth values lower than the threshold are detected as outliers. Based on this result, we propose three new outlier detection procedures. The results of a simulation study show that our proposals generally outperform a battery of competitors. We apply our procedures to a real data set consisting in daily curves of emission levels of nitrogen oxides (NO x ) since it is of interest to identify abnormal NO x levels to take necessary environmental political actions.

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Modelling collocation uncertainty of 3D atmospheric profiles

Cited by 17 publications

References 34 publications

Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment

Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment

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

Functional outlier detection by a local depth with application to NO x levels

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