Henk Eskes, OMI meeting 20-22 June 2006 OMI Nitrogen Dioxide: The KNMI Near-Real Time Product Henk Eskes, Pepijn Veefkind, Folkert Boersma, Ronald van.

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Presentation transcript:

Henk Eskes, OMI meeting June 2006 OMI Nitrogen Dioxide: The KNMI Near-Real Time Product Henk Eskes, Pepijn Veefkind, Folkert Boersma, Ronald van der A, Ellen Brinksma (KNMI) Eric Bucsela, Ed Celarier, Jim Gleason, Mark Wenig (NASA)

Henk Eskes, OMI meeting June 2006 NO2 retrieval Combined retrieval- modelling- assimilation-approach Detailed error estimates Averaging kernels

Henk Eskes, OMI meeting June 2006 OMI near-real time processing DOMINO project: Dutch funding: NIVR, GO-2 program Folkert Boersma, Jan Nov 2005 DOMINO-2 project: July June 2007 Ruud Dirksen

Henk Eskes, OMI meeting June 2006 To provide users with near-real time air pollution monitoring Users include: - environmental agencies - air quality forecasters - GEMS (EU GMES) lead by ECMWF NRT comparison OMI with regional AQ models over Europe - PROMOTE (ESA GMES) - … Purpose (1)

Henk Eskes, OMI meeting June 2006 To generate a long-term consistent dataset from: - GOME ( ) - SCIAMACHY ( ) - OMI ( ) - GOME-2 ( ) KNMI retrieval algorithm for tropospheric NO2 Data publicly available via Described in Boersma et al. (JGR, D04311,2004) Purpose (2)

Henk Eskes, OMI meeting June 2006 Ingredient 1: Daily chemical forecast with OMI NO2 assimilation

Henk Eskes, OMI meeting June 2006 Ingredient 2: Near-real time OMI tropospheric NO2 retrieval NASA/KNMI DOAS algorithm

Henk Eskes, OMI meeting June Find window with smallest variation in initial columns 2. Compute mean column vs. across track viewing angle 3. FFT analysis to smooth Stripe correction

Henk Eskes, OMI meeting June Images available within ~2hrs - data acquisition - downlink - processing - KNMI/NASA DOAS algorithm ~2 hrs - NRT processing time: < 2 minutes Near-real time processing

Henk Eskes, OMI meeting June 2006 Near-real time processing started 7 October 2005 has been quite reliable / robust (2 major events: upgrade ECMWF and TM input file error) Off-line archive: Sep Aug 2005 including Dandelions period Near-real time archive: October present Near-real time processor: first results

Henk Eskes, OMI meeting June 2006 KNMI OMI near-real time NO2, Oct 2005 SundaySaturday

Henk Eskes, OMI meeting June 2006 Chimere OMI overpass time, Oct 2005

Henk Eskes, OMI meeting June 2006 SCIAMACHY, October 2004

Henk Eskes, OMI meeting June 2006 OMI, October 2004

Henk Eskes, OMI meeting June 2006 SCIAMACHY - OMI, October 2004

Henk Eskes, OMI meeting June 2006 SCIAMACHY - OMI, October 2004

Henk Eskes, OMI meeting June 2006 Algorithm Clouds (impact of O2-O2, eg use also Raman), Albedo, Stripes,.. Comparisons SCIAMACHY Regional models like Chimère Operational vs NRT Validation Campaigns like Dandelions, INTEX MaxDOAS, SAOZ,.. Surface obs Promote use of OMI NO2 products Plans

Henk Eskes, OMI meeting June 2006 GOME/SCIA experience retrieval improvements should focus on cloud/aerosol treatment, surface albedo, stratospheric background, profile shape OMI Based on KNMI/NASA operational slant column retrieval and KNMI retrieval/modelling/assimilation approach for AMF Near-real time processing ingredients: 1. daily TM4/5 forecast/assimilation runs 2. retrieval on orbit by orbit basis Operational since 7 October 2005 Conclusions

Henk Eskes, OMI meeting June 2006 NO2 retrieval: error contributions Typical 30-50% error for individual pixels Boersma et al. JGR 2004

Henk Eskes, OMI meeting June 2006 Eleven years of NO2 data KNMI - IASB: GOME, SCIAMACHY, KNMI - NASA: OMI, present Images and detailed data products, including averaging kernels and error estimates, available on the TEMIS and PROMOTE web sites

Henk Eskes, OMI meeting June 2006 Trend over China GOME, 1997SCIA, 2004

Henk Eskes, OMI meeting June 2006 GOME NO2 intercomparison IPCC study: Comparison NO2 retrievals GOME Univ. Bremen (A. Richter) Harvard, Dalhousie (R. Martin) IASB / KNMI

Henk Eskes, OMI meeting June 2006 GOME NO2 intercomparison The three algorithms follow the same approach: 1.DOAS slant column fit 2.Estimate stratospheric part of the slant column 3.Calculate tropospheric AMF based on model-generated profile shapes But have very different building blocks

Henk Eskes, OMI meeting June 2006 GOME NO2 intercomparison IUP BremenDalhousieKNMI/BIRA NsNs 425 – 455 nm nm426.3 – nm N s,st Ref. sector scaled to SLIMCAT strat. Ref. SectorData-assimilation in TM4 Cloud fraction (albedo) FRESCO 0.2 cloud fraction; only cloud selection, no further correction GOMECAT (Kuruso)FRESCO (0.8) Cloud pressure Not usedGOMECATFRESCO Albedo GOME (Koelemeijer) TOMS/GOME (1  x1  ) Profile shape MOZART-2 run for 1997, monthly averages on 2.8 x 2.8 ° GEOS-CHEM TM4 (3  x2  ) Temperature correction No?Yes, ECMWF T- profiles

Henk Eskes, OMI meeting June 2006 SCIAMACHY vs. Chimère: yearly mean 2003 Nadège Blond