Reference Quality Upper-Air Measurements: guidance for developing GRUAN data products

Immler, Franz; Dykema, J. A.; Gardiner, Tom; Whiteman, David N.; Thorne, Peter; Vömel, H.

doi:10.5194/amt-3-1217-2010

Cited by 154 publications

(174 citation statements)

References 13 publications

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“…In addition to these principles, the Global Climate Observing System 2010 (GCOS, 2010) defined observation requirements for essential climate variables, such as upper-air tropospheric and stratospheric temperature. The requirements for the precision and resolution of temperature profiles are less than 0.5 K root-mean-square value, 500 and 0.5 km horizontal and vertical resolutions, respectively, in the upper troposphere and 1.5 km vertical resolution in the lower stratosphere (Immler et al, 2010;Steiner et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Quantifying residual ionospheric errors in GNSS radio occultation bending angles based on ensembles of profiles from end-to-end simulations

et al. 2015

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Abstract. The radio occultation (RO) technique using signals from the Global Navigation Satellite System (GNSS), in particular from the Global Positioning System (GPS) so far, is currently widely used to observe the atmosphere for applications such as numerical weather prediction and global climate monitoring. The ionosphere is a major error source in RO measurements at stratospheric altitudes, and a linear ionospheric correction of dual-frequency RO bending angles is commonly used to remove the first-order ionospheric effect. However, the residual ionospheric error (RIE) can still be significant so that it needs to be further mitigated for high-accuracy applications, especially above about 30 km altitude where the RIE is most relevant compared to the magnitude of the neutral atmospheric bending angle. Quantification and careful analyses for better understanding of the RIE is therefore important for enabling benchmark-quality stratospheric RO retrievals. Here we present such an analysis of bending angle RIEs covering the stratosphere and mesosphere, using quasi-realistic end-to-end simulations for a full-day ensemble of RO events. Based on the ensemble simulations we assessed the variation of bending angle RIEs, both biases and standard deviations, with solar activity, latitudinal region and with or without the assumption of ionospheric spherical symmetry and co-existing observing system errors. We find that the bending angle RIE biases in the upper stratosphere and mesosphere, and in all latitudinal zones from low to high latitudes, have a clear negative tendency and a magnitude increasing with solar activity, which is in line with recent empirical studies based on real RO data although we find smaller bias magnitudes, deserving further study in the future. The maximum RIE biases are found at low latitudes during daytime, where they amount to within −0.03 to −0.05 µrad, the smallest at high latitudes (0 to −0.01 µrad; quiet space weather and winter conditions). Ionospheric spherical symmetry or asymmetries about the RO event location have only a minor influence on RIE biases. The RIE standard deviations are markedly increased both by ionospheric asymmetries and increasing solar activity and amount to about 0.3 to 0.7 µrad in the upper stratosphere and mesosphere. Taking also into account the realistic observation errors of a modern RO receiving system, amounting globally to about 0.4 µrad (unbiased; standard deviation), shows that the random RIEs are typically comparable to the total observing system error. The results help to inform future RIE mitigation schemes that will improve upon the use of the linear ionospheric correction of bending angles and also provide explicit uncertainty estimates.

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Section: Introductionmentioning

confidence: 99%

Quantifying residual ionospheric errors in GNSS radio occultation bending angles based on ensembles of profiles from end-to-end simulations

et al. 2015

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“…For long-term climate observations using frequently changing instruments this stability test prior to launch is essential to gain confidence in the data set (Immler et al, 2010). Although we did not start this test when the older instruments described in Sect.…”

Section: Ground Checkmentioning

confidence: 99%

“…Although they are recognized by many as reference instruments, we refer to the rigorous definition of what constitutes a reference observation given recently by Immler et al (2010). This paper defines reference-quality atmospheric observations as such, which are based on traceability, a detailed analysis of the uncertainty budget, and a detailed knowledge of the calibration procedures and data processing algorithms that are required for determining the uncertainty of each individual data point.…”

Section: Introductionmentioning

confidence: 99%

An update on the uncertainties of water vapor measurements using cryogenic frost point hygrometers

et al. 2016

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Abstract. Long time series of observations of essential climate variables in the troposphere and stratosphere are often impacted by inconsistencies in instrumentation and ambiguities in the interpretation of the data. To reduce these problems of long-term data series, all measurements should include an estimate of their uncertainty and a description of their sources. Here we present an update of the uncertainties for tropospheric and stratospheric water vapor observations using the cryogenic frost point hygrometer (CFH). The largest source of measurement uncertainty is the controller stability, which is discussed here in detail. We describe a method to quantify this uncertainty for each profile based on the measurements. We also show the importance of a manufacturerindependent ground check, which is an essential tool to continuously monitor the uncertainty introduced by instrument variability. A small bias, which has previously been indicated in lower tropospheric measurements, is described here in detail and has been rectified. Under good conditions, the total from all sources of uncertainty of frost point or dew point measurements using the CFH can be better than 0.2 K. Systematic errors, which are most likely to impact long-term climate series, are verified to be less than 0.1 K.The impact of the radiosonde pressure uncertainty on the mixing ratio for properly processed radiosondes is considered small. The mixing ratio uncertainty may be as low as 2 to 3 %. The impact of the ambient temperature uncertainty on relative humidity (RH) is generally larger than that of the frost point uncertainty. The relative RH uncertainty may be as low as 2 % in the lower troposphere and 5 % in the tropical tropopause region.

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“…-The measurements are traceable through an unbroken processing chain (in which the uncertainty arising in each step has been rigorously quantified) to SI units, common reference points defined by BIPM or community recognised standards (ideally recognised by the National Measurement Institute), using best practices documented in the accessible literature (Immler et al, 2010). Dirksen et al (2014) provide an example of the steps required to deliver such a product.…”

Section: Reference-observing Networkmentioning

confidence: 99%

“…A key step to achieving this is to identify, in as unambiguous a manner as possible, those non-satellite measurements that are suitable for such an application. These reference observations must be sufficiently well characterised (JGCM, 2008;Immler et al, 2010;WMO/BIPM, 2010), so that if a difference is found in the satellite data being compared, after accounting for inevitable co-location mismatch effects, we can be confident that the difference arises from the satellite and not from the comparator.…”

Section: Introductionmentioning

confidence: 99%

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

Thorne

Madonna

Schulz

et al. 2017

Geosci. Instrum. Method. Data Syst.

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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.

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Reference Quality Upper-Air Measurements: guidance for developing GRUAN data products

Cited by 154 publications

References 13 publications

Quantifying residual ionospheric errors in GNSS radio occultation bending angles based on ensembles of profiles from end-to-end simulations

Quantifying residual ionospheric errors in GNSS radio occultation bending angles based on ensembles of profiles from end-to-end simulations

An update on the uncertainties of water vapor measurements using cryogenic frost point hygrometers

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

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