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  • 1
    In: Remote Sensing, MDPI AG, Vol. 11, No. 5 ( 2019-02-26), p. 480-
    Abstract: How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question is the key to developing Climate Data Records from the Meteosat Visible and Infrared Imager on board the Meteosat First Generation (MFG) of geostationary satellites, which acquired Earth radiance images in the Visible (VIS) broad band from 1977 to 2017. This article presents a new metrologically sound method for retrieving the VIS spectral response from matchups of pseudo-invariant calibration site (PICS) pixels with datasets of simulated top-of-atmosphere spectral radiance used as reference. Calibration sites include bright desert, open ocean and deep convective cloud targets. The absolute instrument spectral response function is decomposed into generalised Bernstein basis polynomials and a degradation function that is based on plain physical considerations and able to represent typical chromatic ageing characteristics. Retrieval uncertainties are specified in terms of an error covariance matrix, which is projected from model parameter space into the spectral response function domain and range. The retrieval method considers target type-specific biases due to errors in, e.g., the selection of PICS target pixels and the spectral radiance simulation explicitly. It has been tested with artificial and well-comprehended observational data from the Spinning Enhanced Visible and Infrared Imager on-board Meteosat Second Generation and has retrieved meaningful results for all MFG satellites apart from Meteosat-1, which was not available for analysis.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
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  • 2
    In: Remote Sensing, MDPI AG, Vol. 11, No. 9 ( 2019-04-27), p. 1002-
    Abstract: Fundamental and thematic climate data records derived from satellite observations provide unique information for climate monitoring and research. Since any satellite only operates over a relatively short period of time, creating a climate data record also requires the combination of space-borne measurements from a series of several (often similar) satellite sensors. Simply combining calibrated measurements from several sensors can, however, produce an inconsistent climate data record. This is particularly true of older, historic sensors whose behaviour in space was often different from their behaviour during pre-launch calibration and more scientific value can be derived from considering the series of historical and present satellites as a whole. Here, we consider harmonisation as a process that obtains new calibration coefficients for revised sensor calibration models by comparing calibrated measurements over appropriate satellite-to-satellite matchups, such as simultaneous nadir overpasses and which reconciles the calibration of different sensors given their estimated spectral response function differences. We present the concept of a framework that establishes calibration coefficients and their uncertainty and error covariance for an arbitrary number of sensors in a metrologically-rigorous manner. We describe harmonisation and its mathematical formulation as an inverse problem that is extremely challenging when some hundreds of millions of matchups are involved and the errors of fundamental sensor measurements are correlated. We solve the harmonisation problem as marginalised errors in variables regression. The algorithm involves computation of first and second-order partial derivatives using Algorithmic Differentiation. Finally, we present re-calibrated radiances from a series of nine Advanced Very High Resolution Radiometer sensors showing that the new time series has smaller matchup differences compared to the unharmonised case while being consistent with uncertainty statistics.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
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  • 3
    In: Journal of Hydrology, Elsevier BV, Vol. 580 ( 2020-01), p. 124245-
    Type of Medium: Online Resource
    ISSN: 0022-1694
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
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  • 4
    In: Sensors, MDPI AG, Vol. 19, No. 17 ( 2019-08-23), p. 3662-
    Abstract: Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public. However, differences remain among these datasets due to different retrieval methodologies and assumptions. The Quality Assurance for Essential Climate Variables (QA4ECV) project recently developed a quality assurance framework to provide understandable and traceable quality information for Essential Climate Variables (ECVs). The QA4ECV FAPAR is one of these ECVs. The aim of this study is to investigate the capability of QA4ECV FAPAR for drought monitoring in Australia. Through spatial and temporal comparison and correlation analysis with widely used Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour l’Observation de la Terre (SPOT)/PROBA-V FAPAR generated by Copernicus Global Land Service (CGLS), and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index, as well as the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture, the study shows that the QA4ECV FAPAR can support agricultural drought monitoring and assessment in Australia. The traceable and reliable uncertainties associated with the QA4ECV FAPAR provide valuable information for applications that use the QA4ECV FAPAR dataset in the future.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
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  • 5
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 1999
    In:  Journal of Geophysical Research: Oceans Vol. 104, No. C12 ( 1999-12-15), p. 29529-29547
    In: Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), Vol. 104, No. C12 ( 1999-12-15), p. 29529-29547
    Abstract: We first describe the principles and practical considerations behind the computer generation of the adjoint to the Massachusetts Institute of Technology ocean general circulation model (GCM) using R. Giering's software tool Tangent‐Linear and Adjoint Model Compiler (TAMC). The TAMC's recipe for (FORTRAN‐) line‐by‐line generation of adjoint code is explained by interpreting an adjoint model strictly as the operator that gives the sensitivity of the output of a model to its input. Then, the sensitivity of 1993 annual mean heat transport across 29°N in the Atlantic, to the hydrography on January 1, 1993, is calculated from a global solution of the GCM. The “kinematic sensitivity” to initial temperature variations is isolated, showing how the latter would influence heat transport if they did not affect the density and hence the flow. Over 1 year the heat transport at 29°N is influenced kinematically from regions up to 20° upstream in the western boundary current and up to 5° upstream in the interior. In contrast, the dynamical influences of initial temperature (and salinity) perturbations spread from as far as the rim of the Labrador Sea to the 29°N section along the western boundary. The sensitivities calculated with the adjoint compare excellently to those from a perturbation calculation with the dynamical model. Perturbations in initial interior salinity influence meridional overturning and heat transport when they have propagated to the western boundary and can thus influence the integrated east‐west density difference. Our results support the notion that boundary monitoring of meridional mass and heat transports is feasible.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 1999
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  • 6
    Online Resource
    Online Resource
    American Meteorological Society ; 2002
    In:  Journal of Climate Vol. 15, No. 19 ( 2002-10), p. 2721-2739
    In: Journal of Climate, American Meteorological Society, Vol. 15, No. 19 ( 2002-10), p. 2721-2739
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2002
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  • 7
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 1999
    In:  Journal of Geophysical Research: Atmospheres Vol. 104, No. D15 ( 1999-08-20), p. 18535-18553
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 104, No. D15 ( 1999-08-20), p. 18535-18553
    Abstract: TM2 is a global three‐dimensional model of the atmospheric transport of passive tracers. The adjoint of TM2 is a model that allows the efficient evaluation of derivatives of the simulated tracer concentration at observational locations with respect to the tracer's sources and sinks. We describe the generation of the adjoint model by applying the Tangent linear and Adjoint Model Compiler in the reverse mode of automatic differentiation to the code of TM2. Using CO 2 as an example of a chemically inert tracer, the simulated concentration at observational locations is linear in the surface exchange fluxes, and thus the transport can be represented by the model's Jacobian matrix. In many current inverse modeling studies, such a matrix has been computed by multiple runs of a transport model for a set of prescribed surface flux patterns. The computational cost has been proportional to the number of patterns. In contrast, for differentiation in reverse mode, the cost is independent of the number of flux components. Hence, by a single run of the adjoint model, the Jacobian for the approximately 8° latitude by 10° longitude horizontal resolution of TM2 could be computed efficiently. We quantify this efficiency by comparison with the conventional forward modeling approach. For some prominent observational sites, we present visualizations of the Jacobian matrix by series of illustrative global maps quantifying the impact of potential emissions on the concentration in particular months. Furthermore, we demonstrate how the Jacobian matrix is employed to completely analyze a transport model run: A simulated monthly mean value at a particular station is decomposed into the contributions to this value by all flux components, i.e., the fluxes into every surface model grid cell and month. This technique also results in a series of global maps.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 1999
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  • 8
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2000
    In:  Journal of Geophysical Research: Oceans Vol. 105, No. C11 ( 2000-11-15), p. 26063-26087
    In: Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), Vol. 105, No. C11 ( 2000-11-15), p. 26063-26087
    Abstract: Sea surface temperature, sea level, and pseudo wind stress anomaly data from late 1996 to early 1998 are assimilated into an intermediate coupled model of the Tropical Pacific. Model data consistency is examined. Impact of the assimilation on forecast is evaluated. The ocean component of the coupled model consists of a shallow water model with two baroclinic modes, an Ekman shear layer, and a mixed layer temperature equation. The atmospheric model is a statistical one (based on dominant covariance of historical surface temperature and pseudo wind stress anomaly data). The adjoint method is used to fit the coupled model to 6 months of data by optimally adjusting the initial state and model parameters. A forecast is performed using the end state of an assimilation experiment as initial conditions and using parameters estimated during the assimilation period. Thus the model state during the assimilation and that during the forecast belong to the same model trajectory in different periods. Such an initialization procedure is useful in avoiding initial shock during forecast due to inconsistency of an initial state with the coupled model physics. As a result of optimal adjustments of initial state and parameters, the model is able to reproduce observed interannual variability of sea surface temperature and sea level reasonably well. The averaged residual model data misfits over various 6 month periods are 0.5°C and 5 cm, respectively. The model has a limited skill in reproducing much of the off‐equatorial wind anomalies. The residual model data misfit in pseudo wind stress anomaly is larger than 10 m 2 s −2 . Forecasts initialized from the assimilation product are overall more realistic than those simply initialized from wind‐forced ocean states. Consistent improvement due to optimal initialization is found for sea surface temperature and sea level anomalies in the central‐eastern Pacific and zonal pseudo wind stress anomaly in the central Pacific, both in terms of root‐mean‐squared deviation from and correlation with the data. The adjustments of parameters in addition to initial state in a coupled context is found to be important to improving the model data consistency during the assimilation and the forecast. In particular, the estimated drag and damping coefficients properly regulate the relative strength of forcing and damping of the ocean state so as to fit the three types of observations during the assimilation (initialization) period, which facilitates the development of a large‐amplitude warming event during the forecast. The study demonstrates the utility of oceanic and atmospheric data to estimate initial state and model parameters in a coupled context, which is useful to the evaluation, improvement, and initialization of El Niño‐Southern Oscillation forecast models.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2000
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  • 9
    Online Resource
    Online Resource
    Elsevier BV ; 2005
    In:  Future Generation Computer Systems Vol. 21, No. 8 ( 2005-10), p. 1356-1371
    In: Future Generation Computer Systems, Elsevier BV, Vol. 21, No. 8 ( 2005-10), p. 1356-1371
    Type of Medium: Online Resource
    ISSN: 0167-739X
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2005
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  • 10
    In: Remote Sensing, MDPI AG, Vol. 10, No. 8 ( 2018-08-09), p. 1254-
    Abstract: Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
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