000056573 001__ 56573
000056573 005__ 20240712101027.0
000056573 0247_ $$2WOS$$aWOS:000239137200002
000056573 0247_ $$2doi$$a10.5194/acp-6-2943-2006
000056573 0247_ $$2Handle$$a2128/8679
000056573 0247_ $$2altmetric$$aaltmetric:8845286
000056573 037__ $$aPreJuSER-56573
000056573 041__ $$aeng
000056573 082__ $$a550
000056573 084__ $$2WoS$$aMeteorology & Atmospheric Sciences
000056573 1001_ $$0P:(DE-HGF)0$$avan Noije, T. P. C.$$b0
000056573 245__ $$aMulti-model ensemble simulations of troposphere NO2 compared with GOME retrievals for the year 2000
000056573 260__ $$aKatlenburg-Lindau$$bEGU$$c2006
000056573 300__ $$a2943 - 2979
000056573 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
000056573 3367_ $$2DataCite$$aOutput Types/Journal article
000056573 3367_ $$00$$2EndNote$$aJournal Article
000056573 3367_ $$2BibTeX$$aARTICLE
000056573 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000056573 3367_ $$2DRIVER$$aarticle
000056573 4001_ $$aNoije, T. P. C.
000056573 440_0 $$09601$$aAtmospheric Chemistry and Physics$$v6$$x1680-7316
000056573 500__ $$aRecord converted from VDB: 12.11.2012
000056573 520__ $$aWe present a systematic comparison of tropospheric NO2 from 17 global atmospheric chemistry models with three state-of-the-art retrievals from the Global Ozone Monitoring Experiment (GOME) for the year 2000. The models used constant anthropogenic emissions from IIASA/EDGAR3.2 and monthly emissions from biomass burning based on the 1997 - 2002 average carbon emissions from the Global Fire Emissions Database (GFED). Model output is analyzed at 10: 30 local time, close to the overpass time of the ERS-2 satellite, and collocated with the measurements to account for sampling biases due to incomplete spatiotemporal coverage of the instrument. We assessed the importance of different contributions to the sampling bias: correlations on seasonal time scale give rise to a positive bias of 30 - 50% in the retrieved annual means over regions dominated by emissions from biomass burning. Over the industrial regions of the eastern United States, Europe and eastern China the retrieved annual means have a negative bias with significant contributions ( between - 25% and + 10% of the NO2 column) resulting from correlations on time scales from a day to a month. We present global maps of modeled and retrieved annual mean NO2 column densities, together with the corresponding ensemble means and standard deviations for models and retrievals. The spatial correlation between the individual models and retrievals are high, typically in the range 0.81 - 0.93 after smoothing the data to a common resolution. On average the models underestimate the retrievals in industrial regions, especially over eastern China and over the Highveld region of South Africa, and overestimate the retrievals in regions dominated by biomass burning during the dry season. The discrepancy over South America south of the Amazon disappears when we use the GFED emissions specific to the year 2000. The seasonal cycle is analyzed in detail for eight different continental regions. Over regions dominated by biomass burning, the timing of the seasonal cycle is generally well reproduced by the models. However, over Central Africa south of the Equator the models peak one to two months earlier than the retrievals. We further evaluate a recent proposal to reduce the NOx emission factors for savanna fires by 40% and find that this leads to an improvement of the amplitude of the seasonal cycle over the biomass burning regions of Northern and Central Africa. In these regions the models tend to underestimate the retrievals during the wet season, suggesting that the soil emissions are higher than assumed in the models. In general, the discrepancies between models and retrievals cannot be explained by a priori profile assumptions made in the retrievals, neither by diurnal variations in anthropogenic emissions, which lead to a marginal reduction of the NO2 abundance at 10: 30 local time ( by 2.5 - 4.1% over Europe). Overall, there are significant differences among the various models and, in particular, among the three retrievals. The discrepancies among the retrievals ( 10 - 50% in the annual mean over polluted regions) indicate that the previously estimated retrieval uncertainties have a large systematic component. Our findings imply that top-down estimations of NOx emissions from satellite retrievals of tropospheric NO2 are strongly dependent on the choice of model and retrieval.
000056573 536__ $$0G:(DE-Juel1)FUEK406$$2G:(DE-HGF)$$aAtmosphäre und Klima$$cP22$$x0
000056573 588__ $$aDataset connected to Web of Science
000056573 650_7 $$2WoSType$$aJ
000056573 7001_ $$0P:(DE-HGF)0$$aEskes, H.J.$$b1
000056573 7001_ $$0P:(DE-HGF)0$$aDentener, F. J.$$b2
000056573 7001_ $$0P:(DE-HGF)0$$aStevenson, D. S.$$b3
000056573 7001_ $$0P:(DE-HGF)0$$aEllingsen, K.$$b4
000056573 7001_ $$0P:(DE-Juel1)6952$$aSchultz, M. G.$$b5$$uFZJ
000056573 7001_ $$0P:(DE-HGF)0$$aWild, O.$$b6
000056573 7001_ $$0P:(DE-HGF)0$$aAmann, M.$$b7
000056573 7001_ $$0P:(DE-HGF)0$$aAtherton, C. S.$$b8
000056573 7001_ $$0P:(DE-HGF)0$$aBergmann, D. J.$$b9
000056573 7001_ $$0P:(DE-HGF)0$$aBey, I.$$b10
000056573 7001_ $$0P:(DE-HGF)0$$aBoersma, K. F.$$b11
000056573 7001_ $$0P:(DE-HGF)0$$aButler, T.$$b12
000056573 7001_ $$0P:(DE-HGF)0$$aCofala, J.$$b13
000056573 7001_ $$0P:(DE-HGF)0$$aDrevet, J.$$b14
000056573 7001_ $$0P:(DE-HGF)0$$aFiore, A. M.$$b15
000056573 7001_ $$0P:(DE-HGF)0$$aGauss, M.$$b16
000056573 7001_ $$0P:(DE-HGF)0$$aHauglustaine, D. A.$$b17
000056573 7001_ $$0P:(DE-HGF)0$$aHorowitz, L. W.$$b18
000056573 7001_ $$0P:(DE-HGF)0$$aIsaksen, I. S. A.$$b19
000056573 7001_ $$0P:(DE-HGF)0$$aKrol, M. C.$$b20
000056573 7001_ $$0P:(DE-HGF)0$$aLamarque, J.-F.$$b21
000056573 7001_ $$0P:(DE-HGF)0$$aLawrence, M. G.$$b22
000056573 7001_ $$0P:(DE-HGF)0$$aMartin, R. V.$$b23
000056573 7001_ $$0P:(DE-HGF)0$$aMontanaro, V.$$b24
000056573 7001_ $$0P:(DE-HGF)0$$aMüller, J.-F.$$b25
000056573 7001_ $$0P:(DE-HGF)0$$aPitari, G.$$b26
000056573 7001_ $$0P:(DE-HGF)0$$aPrather, M. J.$$b27
000056573 7001_ $$0P:(DE-HGF)0$$aPyle, J. A.$$b28
000056573 7001_ $$0P:(DE-HGF)0$$aRichter, A.$$b29
000056573 7001_ $$0P:(DE-HGF)0$$aRodriguez, J. M.$$b30
000056573 7001_ $$0P:(DE-HGF)0$$aSavage, N. H.$$b31
000056573 7001_ $$0P:(DE-HGF)0$$aStrahan, S.E.$$b32
000056573 7001_ $$0P:(DE-HGF)0$$aSudo, K.$$b33
000056573 7001_ $$0P:(DE-HGF)0$$aSzopa, S.$$b34
000056573 7001_ $$0P:(DE-HGF)0$$avan Roozendael, M.$$b35
000056573 773__ $$0PERI:(DE-600)2069847-1$$a10.5194/acp-6-2943-2006$$gVol. 6, p. 2943 - 2979$$p2943 - 2979$$q6<2943 - 2979$$tAtmospheric chemistry and physics$$v6$$x1680-7316$$y2006
000056573 8564_ $$uhttps://juser.fz-juelich.de/record/56573/files/acp-6-2943-2006.pdf$$yOpenAccess
000056573 8564_ $$uhttps://juser.fz-juelich.de/record/56573/files/acp-6-2943-2006.gif?subformat=icon$$xicon$$yOpenAccess
000056573 8564_ $$uhttps://juser.fz-juelich.de/record/56573/files/acp-6-2943-2006.jpg?subformat=icon-180$$xicon-180$$yOpenAccess
000056573 8564_ $$uhttps://juser.fz-juelich.de/record/56573/files/acp-6-2943-2006.jpg?subformat=icon-700$$xicon-700$$yOpenAccess
000056573 8564_ $$uhttps://juser.fz-juelich.de/record/56573/files/acp-6-2943-2006.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000056573 909CO $$ooai:juser.fz-juelich.de:56573$$pdnbdelivery$$pVDB$$pdriver$$popen_access$$popenaire
000056573 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed
000056573 915__ $$0StatID:(DE-HGF)0510$$aOpenAccess
000056573 915__ $$0LIC:(DE-HGF)CCBYNCSA2$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-ShareAlike CC BY-NC-SA 2.0
000056573 9141_ $$aNachtrag$$y2006
000056573 9131_ $$0G:(DE-Juel1)FUEK406$$bUmwelt$$kP22$$lAtmosphäre und Klima$$vAtmosphäre und Klima$$x0$$zfortgesetzt als P23
000056573 9201_ $$0I:(DE-Juel1)VDB48$$d31.12.2006$$gICG$$kICG-II$$lTroposphäre$$x0
000056573 970__ $$aVDB:(DE-Juel1)88824
000056573 9801_ $$aFullTexts
000056573 980__ $$aFullTexts
000056573 980__ $$aConvertedRecord
000056573 980__ $$ajournal
000056573 980__ $$aI:(DE-Juel1)IEK-8-20101013
000056573 980__ $$aVDB
000056573 980__ $$aUNRESTRICTED
000056573 981__ $$aI:(DE-Juel1)ICE-3-20101013
000056573 981__ $$aI:(DE-Juel1)IEK-8-20101013