Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV-Vis tropospheric column retrievals
Boersma, K.F. ; Vinken, G.C.M. ; Eskes, H.J. - \ 2016
Geoscientific Model Development 9 (2016)2. - ISSN 1991-959X - p. 875 - 898.

Ultraviolet-visible (UV-Vis) satellite retrievals of trace gas columns of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, and to provide top-down constraints on emissions. However, because models and satellite measurements do not represent the exact same geophysical quantities, the process of confronting model fields with satellite measurements is complicated by representativeness errors, which degrade the quality of the comparison beyond contributions from modelling and measurement errors alone. Here we discuss three types of representativeness errors that arise from the act of carrying out a model-satellite comparison: (1) horizontal representativeness errors due to imperfect collocation of the model grid cell and an ensemble of satellite pixels called superobservation, (2) temporal representativeness errors originating mostly from differences in cloud cover between the modelled and observed state, and (3) vertical representativeness errors because of reduced satellite sensitivity towards the surface accompanied with necessary retrieval assumptions on the state of the atmosphere. To minimize the impact of these representativeness errors, we recommend that models and satellite measurements be sampled as consistently as possible, and our paper provides a number of recipes to do so. A practical confrontation of tropospheric NO2 columns simulated by the TM5 chemistry transport model (CTM) with Ozone Monitoring Instrument (OMI) tropospheric NO2 retrievals suggests that horizontal representativeness errors, while unavoidable, are limited to within 5-10 % in most cases and of random nature. These errors should be included along with the individual retrieval errors in the overall superobservation error. Temporal sampling errors from mismatches in cloud cover, and, consequently, in photolysis rates, are of the order of 10 % for NO2 and HCHO, and systematic, but partly avoidable. In the case of air pollution applications where sensitivity down to the ground is required, we recommend that models should be sampled on the same mostly cloud-free days as the satellite retrievals. The most relevant representativeness error is associated with the vertical sensitivity of UV-Vis satellite retrievals. Simple vertical integration of modelled profiles leads to systematically different model columns compared to application of the appropriate averaging kernel. In comparing OMI NO2 to GEOS-Chem NO2 simulations, these systematic differences are as large as 15-20 % in summer, but, again, avoidable.

Multimodel ensemble simulations of present-day and near-future tropospheric ozone
Stevenson, D.S. ; Dentener, F.J. ; Schultz, M.G. ; Ellingsen, K. ; Noije, T.P.C. van; Wild, O. ; Zeng, G. ; Amann, M. ; Atherton, C.S. ; Bell, N. ; Bergmann, D.J. ; Bey, I. ; Butler, T. ; Cofala, J. ; Collins, W.J. ; Derwent, R.G. ; Doherty, R.M. ; Drevet, J. ; Eskes, H.J. ; Fiore, A.M. ; Gauss, M. ; Hauglustaine, D.A. ; Horowitz, L.W. ; Isaksen, I.S.A. ; Krol, M.C. ; Lamarque, J.F. ; Lawrence, M.G. ; Montanaro, V. ; Muller, J.F. ; Pitari, G. ; Prather, M.J. ; Pyle, J.A. ; Rast, S. ; Rodriguez, J.M. ; Sanderson, M.G. ; Savage, N.H. ; Shindell, D.T. ; Strahan, S.E. ; Sudo, K. ; Szopa, S. - \ 2006
Journal of Geophysical Research: Atmospheres 111 (2006). - ISSN 2169-897X - p. D08301 - D08301.
chemistry transport models - general-circulation model - biogenic nox emissions - global chemical-model - aircraft mozaic data - climate-change - nonmethane hydrocarbons - methane emissions - surface ozone - atmospheric chemistry
Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state-of-the-art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions scenarios, broadly representing “optimistic,” “likely,” and “pessimistic” options, are compared to a base year 2000 simulation. This base case realistically represents the current global distribution of tropospheric ozone. A further set of simulations considers the influence of climate change over the same time period by forcing the central emissions scenario with a surface warming of around 0.7K. The use of a large multimodel ensemble allows us to identify key areas of uncertainty and improves the robustness of the results. Ensemble mean changes in tropospheric ozone burden between 2000 and 2030 for the 3 scenarios range from a 5% decrease, through a 6% increase, to a 15% increase. The intermodel uncertainty (±1 standard deviation) associated with these values is about ±25%. Model outliers have no significant influence on the ensemble mean results. Combining ozone and methane changes, the three scenarios produce radiative forcings of -50, 180, and 300 mW m-2, compared to a CO2 forcing over the same time period of 800–1100 mW m-2. These values indicate the importance of air pollution emissions in short- to medium-term climate forcing and the potential for stringent/lax control measures to improve/worsen future climate forcing. The model sensitivity of ozone to imposed climate change varies between models but modulates zonal mean mixing ratios by ±5 ppbv via a variety of feedback mechanisms, in particular those involving water vapor and stratosphere-troposphere exchange. This level of climate change also reduces the methane lifetime by around 4%. The ensemble mean year 2000 tropospheric ozone budget indicates chemical production, chemical destruction, dry deposition and stratospheric input fluxes of 5100, 4650, 1000, and 550 Tg(O3) yr-1, respectively. These values are significantly different to the mean budget documented by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR). The mean ozone burden (340 Tg(O3)) is 10% larger than the IPCC TAR estimate, while the mean ozone lifetime (22 days) is 10% shorter. Results from individual models show a correlation between ozone burden and lifetime, and each model's ozone burden and lifetime respond in similar ways across the emissions scenarios. The response to climate change is much less consistent. Models show more variability in the tropics compared to midlatitudes. Some of the most uncertain areas of the models include treatments of deep tropical convection, including lightning NO x production; isoprene emissions from vegetation and isoprene's degradation chemistry; stratosphere-troposphere exchange; biomass burning; and water vapor concentrations.
Multi-model ensemble simulations of troposheric NO2 compared with GOME retrievals for the year 2000
Noije, T.P.C. van; Eskes, H.J. ; Dentener, F.J. ; Stevenson, D.S. ; Ellingsen, K. ; Schultz, M.G. ; Wild, O. ; Amann, M. ; Atherton, C.S. ; Bergmann, D. ; Bey, I. ; Boersma, K.F. ; Butler, T. ; Cofala, J. ; Drevet, J. ; Fiore, A.M. ; Gauss, M. ; Hauglustaine, D.A. ; Horowitz, L.W. ; Isaksen, I.S.A. ; Krol, M.C. ; Lamarque, J.F. ; Lawrence, M.G. ; Martin, R.V. ; Montanaro, V. ; Muller, J.F. ; Pitari, G. ; Prather, M.J. ; Pyle, J.A. ; Richter, A. ; Rodriguez, J.M. ; Savage, N.H. ; Strahan, S.E. ; Sudo, K. ; Szopa, S. ; Roozendael, M. van - \ 2006
Atmospheric Chemistry and Physics 6 (2006)10. - ISSN 1680-7316 - p. 2943 - 2979.
chemical-transport model - ozone monitoring experiment - radiative-transfer model - aircraft mozaic data - satellite-observations - nitrogen-dioxide - nonmethane hydrocarbons - surface reflectivity - global distributions - 3-dimensional model
We 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.
Multimodel simulations of carbon monoxide: Comparison with observations and projected near-future changes
Shindell, D.T. ; Faluvegi, G. ; Stevenson, D.S. ; Krol, M.C. ; Emmons, L.K. ; Lamarque, J.F. ; Petron, G. ; Dentener, F.J. ; Ellingsen, K. ; Schultz, M.G. ; Wild, O. ; Amann, M. ; Atherton, C.S. ; Bergmann, D.J. ; Bey, I. ; Butler, T. ; Cofala, J. ; Collins, W.J. ; Derwent, R.G. ; Doherty, R.M. ; Drevet, J. ; Eskes, H.J. ; Fiore, A.M. ; Gauss, M. ; Hauglustaine, D.A. ; Horowitz, L.W. ; Isaksen, I.S.A. ; Lawrence, M.G. ; Montanaro, V. ; Muller, J.F. ; Pitari, G. ; Prather, M.J. ; Pyle, J.A. ; Rast, S. ; Rodriguez, J.M. ; Sanderson, M.G. ; Savage, N.H. ; Strahan, S.E. ; Sudo, K. ; Szopa, S. ; Unger, N. ; Noije, T.P.C. van; Zeng, G. - \ 2006
Journal of Geophysical Research: Atmospheres 111 (2006). - ISSN 2169-897X - 24 p.
chemical-transport model - stratosphere-troposphere exchange - general-circulation model - aircraft mozaic data - nonmethane hydrocarbons - ozone simulations - methane emissions - western pacific - climate-change - 3-d models
We analyze present-day and future carbon monoxide (CO) simulations in 26 state-of-the-art atmospheric chemistry models run to study future air quality and climate change. In comparison with near-global satellite observations from the MOPITT instrument and local surface measurements, the models show large underestimates of Northern Hemisphere (NH) extratropical CO, while typically performing reasonably well elsewhere. The results suggest that year-round emissions, probably from fossil fuel burning in east Asia and seasonal biomass burning emissions in south-central Africa, are greatly underestimated in current inventories such as IIASA and EDGAR3.2. Variability among models is large, likely resulting primarily from intermodel differences in representations and emissions of nonmethane volatile organic compounds (NMVOCs) and in hydrologic cycles, which affect OH and soluble hydrocarbon intermediates. Global mean projections of the 2030 CO response to emissions changes are quite robust. Global mean midtropospheric (500 hPa) CO increases by 12.6 +/- 3.5 ppbv (16%) for the high-emissions (A2) scenario, by 1.7 +/- 1.8 ppbv (2%) for the midrange (CLE) scenario, and decreases by 8.1 +/- 2.3 ppbv (11%) for the low-emissions (MFR) scenario. Projected 2030 climate changes decrease global 500 hPa CO by 1.4 +/- 1.4 ppbv. Local changes can be much larger. In response to climate change, substantial effects are seen in the tropics, but intermodel variability is quite large. The regional CO responses to emissions changes are robust across models, however. These range from decreases of 10-20 ppbv over much of the industrialized NH for the CLE scenario to CO increases worldwide and year-round under A2, with the largest changes over central Africa (20-30 ppbv), southern Brazil (20-35 ppbv) and south and east Asia (30-70 ppbv). The trajectory of future emissions thus has the potential to profoundly affect air quality over most of the world's populated areas.
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