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• W4322005401 abstract "This work was developed on the scope of the national initiative of the Integrated Greenhouse Gas Monitoring System for Germany &#8211; ITMS, which focus on reducing and characterizing uncertainties/errors introduced in the full retrieval chain of models, making use of observational data.&#160;Determining the magnitude, cause, and agents of carbon fluxes is important to advance our current understanding of the carbon budget and cycle, permitting more accurate predictions of its future behaviour. Sources and sinks of CO2at the Earth's surface can, in principle, be estimated from atmospheric concentrations by inverting atmospheric transport in the atmospheric tracer inversions.Solving for CO2 fluxes in the inversions is highly desirable to better understand the carbon cycle but also to support policies aimed at reducing CO2 emissions. The Jena CarboScope inversion developed based on Bayesian inverse methods is used to obtain data-driven estimates of trace gas exchange, quantifying the large-scale sources and sinks of CO2.To make Jena CarboScope estimates more reliable in understanding sources, sinks and transport of atmospheric CO2from the surface into the troposphere, the reliability of this data product should be evaluated based on independent observations. Quantifying the quality of the inversion estimation by decomposing the inherent uncertainty components is a challenging and key component in product reliability and its use. The overall objective in validating and evaluating uncertainties of the Bayesian data product provided by Jena CarboScope, is to explicitly answer the question: How good is the inversion estimation?The assessment of these products is of special importance for further development and possibly allows for judging the trustworthiness of the inversion outcome.This study explores the potential of CarboScope to reproduce CO2 concentrations recorded during regular flights and aircraft campaigns during the past two decades. The inversion estimations are accomplished by forward runs performed with the inversion having the measurement locations as receptors.This study examines biases and uncertainties in the CarboScope estimations evaluated against flights&#8217; data. It has been found that the CO2 simulated by CarboScope in the forward run (using the transport model TM3 for background concentration and STILT for regional signal) agree reasonably well, into the 10/90th percentile for 3-sigma of the distribution. On the other hand, the inversion exhibit some systematic biases at the edges of the distribution under and overestimating at high and lower mixing ratios, respectively.&#160;The CarboScope strength and concerns were enhanced by understanding the differences among observations and the inversion estimation. In comprehensive statistics comparing measurement data from hundreds of flights, we assess the compliance CarboScope`s CO2 estimation. Furthermore, we discuss the estimation and observation mismatches, exploiting the model constraints to reproduce atmospheric transport from the boundary layer to the upper troposphere.&#160;Understanding such constraints has the potential to reduce uncertainties of the atmospheric inversion estimates.&#160;" @default.
• W4322005401 created "2023-02-26" @default.
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• W4322005401 date "2023-05-15" @default.
• W4322005401 modified "2023-09-29" @default.
• W4322005401 title "Using aircraft observations of atmospheric CO2 to evaluate vertical transport within the CarboScope Regional inverse model." @default.
• W4322005401 doi "https://doi.org/10.5194/egusphere-egu23-6978" @default.
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