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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We conduct an inverse modeling analysis of measurements of atmospheric COfrom the TES and MOPITT satellite instruments using the GEOS-Chem globalchemical transport model to quantify emissions of CO in the tropics inNovember 2004. We also assess the consistency of the information provided byTES and MOPITT on surface emissions of CO. We focus on the tropics inNovember 2004, during the biomass burning season, because TES observationsof CO and O<sub>3</sub> and MOPITT observations of CO reveal significantly greaterabundances of these gases than simulated by the GEOS-Chem model during thatperiod. We find that both datasets suggest substantially greater emissionsof CO from sub-equatorial Africa and the Indonesian/Australian region thanin the climatological emissions in the model. The a posteriori emissionsfrom sub-equatorial Africa based on TES and MOPITT data were 173 Tg CO/yrand 184 Tg CO/yr, respectively, compared to the a priori of 95 Tg CO/yr.In the Indonesian/Australian region, the a posteriori emissions inferred fromTES and MOPITT data were 155 Tg CO/yr and 185 Tg CO/yr, respectively,whereas the a priori was 69 Tg CO/yr. The differences between the aposteriori emission estimates obtained from the two datasets are generallyless than 20%. The a posteriori emissions significantly improve thesimulated distribution of CO, however, large regional residuals remain, andare likely due to systematic errors in the analysis. Reducing theseresiduals and improving the accuracy of top-down emission estimates willrequire better characterization of systematic errors in the observations andthe model (chemistry and transport)

atmospheric chemistry and physics

The zonal structure of tropical O&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; and CO as observed by the Tropospheric Emission Spectrometer in November 2004 – Part 1: Inverse modeling of CO emissions