The two-way nested global chemistry-transport zoom model TM5: algorithm and applications

Krol, Maarten; Houweling, S.; Bregman, B.; Broek, Maarten van den; Segers, A.; Velthoven, P. van; Peters, W.; Dentener, Frank; Bergamaschi, P.

doi:10.5194/acpd-4-3975-2004

Cited by 118 publications

(162 citation statements)

References 26 publications

(26 reference statements)

Supporting

Mentioning

158

Contrasting

Order By: Relevance

“…In TM4, boundary layer mixing follows the vertical diffusion parameterization of Holtslag and Moeng [1991]. Diffusion coefficients and mixing depths are updated every 3 h as described by Krol et al [2005]. To investigate the effect of increased mixing layer depth, we compared tropospheric AMFs computed with NO 2 profiles sampled at 1000 and at 1330 LT, but otherwise identical forward model parameters (albedo and cloud inputs) as in the actual retrievals for August 2006.…”

Section: Sciamachy Versus Omi Differences In No X Source Regionsmentioning

confidence: 99%

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

et al. 2008

View full text Add to dashboard Cite

[1] Concurrent (August 2006) measurements of tropospheric NO 2 columns from OMI aboard Aura (1330 local overpass time) and SCIAMACHY aboard Envisat (1000 local overpass time) offer an opportunity to examine the consistency between the two instruments under tropospheric background conditions and the effect of different observing times. For scenes with tropospheric NO 2 columns <5.0 Â 10 15 molecules cm À2 , SCIAMACHY and OMI agree within 1.0-2.0 Â 10 15 molecules cm À2 , consistent with the detection limits of both instruments. We find evidence for a low bias of 0.2 Â 10 15 molecules cm À2 in OMI observations over remote oceans. Over the fossil fuel source regions at northern midlatitudes, we find that SCIAMACHY observes up to 40% higher NO 2 at 1000 local time (LT) than OMI at 1330 LT. Over biomass burning regions in the tropics, SCIAMACHY observes up to 40% lower NO 2 columns than OMI. These differences are present in the spectral fitting of the data (slant column) and are augmented in the fossil fuel regions and dampened in the tropical biomass burning regions by the expected increase in air mass factor as the mixing depth rises from 1000 to 1330 LT. Using a global 3-D chemical transport model (GEOS-Chem), we show that the 1000-1330 LT decrease in tropospheric NO 2 column over fossil fuel source regions can be explained by photochemical loss, dampened by the diurnal cycle of anthropogenic emissions that has a broad daytime maximum. The observed 1000-1330 LT NO 2 column increase over tropical biomass burning regions points to a sharp midday peak in emissions and is consistent with a diurnal cycle of emissions derived from geostationary satellite fire counts.

show abstract

Section: Sciamachy Versus Omi Differences In No X Source Regionsmentioning

confidence: 99%

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

et al. 2008

View full text Add to dashboard Cite

show abstract

“…The TM5 model is an off-line global transport chemistry model Krol et al, 2005;Peters et al, 2004) driven by meteorological ECMWF (European Centre for Medium-Range Weather Forecasts) data. The presently used configuration of TM5 has a spatial global resolution of 6 • ×4 • and a two-way zooming algorithm that allows resolving regions, e.g.…”

Section: The Nested Tm5 Modelmentioning

confidence: 99%

The sensitivity of aerosol in Europe to two different emission inventories and temporal distribution of emissions

et al. 2006

Self Cite

View full text Add to dashboard Cite

Abstract. The sensitivity to two different emission inventories, injection altitude and temporal variations of anthropogenic emissions in aerosol modelling is studied, using the two way nested global transport chemistry model TM5 focussing on Europe in June and December 2000. The simulations of gas and aerosol concentrations and aerosol optical depth (AOD) with the EMEP and AEROCOM emission inventories are compared with EMEP gas and aerosol surface based measurements, AERONET sun photometers retrievals and MODIS satellite data.For the aerosol precursor gases SO 2 and NO x in both months the model results calculated with the EMEP inventory agree better (overestimated by a factor 1.3 for both SO 2 and NO x ) with the EMEP measurements than the simulation with the AEROCOM inventory (overestimated by a factor 2.4 and 1.9, respectively).Besides the differences in total emissions between the two inventories, an important role is also played by the vertical distribution of SO 2 and NO x emissions in understanding the differences between the EMEP and AEROCOM inventories.In December NO x and SO 2 from both simulations agree within 50% with observations. In June SO = 4 evaluated with the EMEP emission inventory agrees slightly better with surface observations than the AE-ROCOM simulation, whereas in December the use of both inventories results in an underestimate of SO4 with a factor 2. Nitrate aerosol measured in summer is not reliable, however in December nitrate aerosol calculations with the EMEP and AEROCOM emissions agree with 30%, and 60%, respectively with the filter measurements. Differences are caused by the total emissions and the temporal distribution of the aerosol precursor gases NO x and NH 3 . Despite these differences, we show that the column integrated AOD is less sensitive to the underlying emission inventories. Calculated AOD Correspondence to: A. de Meij (alexander.de-meij@jrc.it) values with both emission inventories underestimate the observed AERONET AOD values by 20-30%, whereas a case study using MODIS data shows a high spatial agreement.Our evaluation of the role of temporal distribution of anthropogenic emissions on aerosol calculations shows that the daily and weekly temporal distributions of the emissions are only important for NO x , NH 3 and aerosol nitrate. However, for all aerosol species SO = 4 , NH + 4 , POM, BC, as well as for AOD, the seasonal temporal variations used in the emission inventory are important. Our study shows the value of including at least seasonal information on anthropogenic emissions, although from a comparison with a range of measurements it is often difficult to firmly identify the superiority of specific emission inventories, since other modelling uncertainties, e.g. related to transport, aerosol removal, water uptake, and model resolution, play a dominant role.

show abstract

“…This coupled system delivers daily forecasts for reactive trace gases. The models MOCAGE (Josse et al, 2004;Bousserez et al, 2007) and TM5 (Krol et al, 2005) have been running in an offline mode and in experimental phase in a forecast mode coupled to IFS.…”

Section: Introductionmentioning

confidence: 99%

Comparison of OMI NO<sub>2</sub> tropospheric columns with an ensemble of global and European regional air quality models

et al. 2010

View full text Add to dashboard Cite

Abstract. We present a comparison of tropospheric NO 2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008-June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO 2 observations, with a correlation r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared Correspondence to: V. Huijnen (huijnen@knmi.nl) to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO 2 columns of individual RAQ models from the mean were in the range of 20-34% in winter and 40-62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months.The ensemble median shows a stronger seasonal cycle of NO 2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO 2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%.Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small.Published by Copernicus Publications on behalf of the European Geosciences Union. V. Huijnen et al.:Comparison of NO 2 in regional and global models to OMI However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models.In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effec...

show abstract

The two-way nested global chemistry-transport zoom model TM5: algorithm and applications

Cited by 118 publications

References 26 publications

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

The sensitivity of aerosol in Europe to two different emission inventories and temporal distribution of emissions

Comparison of OMI NO<sub>2</sub> tropospheric columns with an ensemble of global and European regional air quality models

Contact Info

Product

Resources

About

The two-way nested global chemistry-transport zoom model TM5: algorithm and applications

Cited by 118 publications

References 26 publications

Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space

Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space

The sensitivity of aerosol in Europe to two different emission inventories and temporal distribution of emissions

Comparison of OMI NO&lt;sub&gt;2&lt;/sub&gt; tropospheric columns with an ensemble of global and European regional air quality models

Contact Info

Product

Resources

About

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

Intercomparison of SCIAMACHY and OMI tropospheric NO₂ columns: Observing the diurnal evolution of chemistry and emissions from space

Comparison of OMI NO<sub>2</sub> tropospheric columns with an ensemble of global and European regional air quality models