English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

. This study assesses the impact of differentstate of the art global biospheric CO2 flux models, when applied asprior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2(OCO-2) observations. This is done with a series of observing systemsimulation experiments (OSSEs) using synthetic CO2 column-average dryair mole fraction ( XCO2 ) retrievals sampled at the OCO-2 satellitespatiotemporal frequency. The OSSEs utilized a 4-D variational(4D-Var) assimilation system with the GEOS-Chem global chemical transportmodel (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes usingsynthetic OCO-2 observations. The impact of biosphere models in inversemodel estimates of NEE is quantified by conducting OSSEs using theNASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEEfrom the multi-model ensemble mean of the Multiscale Synthesis andTerrestrial Model Intercomparison Project as the “truth”. Results showthat the assimilation of simulated XCO2 retrievals at OCO-2 observingmodes over land results in posterior NEE estimates which generally reproduce“true” NEE globally and over terrestrial TransCom-3 regions that arewell-sampled. However, we find larger spread among posterior NEE estimates,when using different prior NEE fluxes, in regions and seasons that havelimited OCO-2 observational coverage and a large range in “bottom-up” NEEfluxes. Seasonally averaged posterior NEE estimates had standard deviations(SD) of ∼10  % to ∼50  % of themulti-model-mean NEE for different TransCom-3 land regions with significantNEE fluxes (regions/seasons with a NEE flux ≥0.5  PgC yr −1 ). On aglobal average, the seasonally averaged residual impact of the prior modelNEE assumption on the posterior NEE spread is ∼10  %–20 % of theposterior NEE mean. Additional OCO-2 OSSE simulations demonstrate thatposterior NEE estimates are also sensitive to the assumed prior NEE fluxuncertainty statistics, with spread in posterior NEE estimates similar tothose when using variable prior model NEE fluxes. In fact, the sensitivityof posterior NEE estimates to prior error statistics was larger thanprior flux values in some regions/times in the tropics and SouthernHemisphere where sufficient OCO-2 data were available and large differencesbetween the prior and truth were evident. Overall, even with theavailability of spatiotemporally dense OCO-2 data, noticeable residualdifferences (up to ∼20  %–30 % globally and 50 % regionally)in posterior NEE flux estimates remain that were caused by the choice ofprior model flux values and the specification of prior flux uncertainties.

Prior biosphere model impact on global terrestrial CO&lt;sub&gt;2&lt;/sub&gt; fluxes estimated from OCO-2 retrievals

Prior biosphere model impact on global terrestrial CO<sub>2</sub> fluxes estimated from OCO-2 retrievals