Henk Eskes

Multimodel ensemble simulations of present-day and near-future tropospheric ozone

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 CO 2 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(O 3 ) 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(O 3 )) 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 models 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 isoprenes degradation chemistry; stratosphere-troposphere exchange; biomass burning; and water vapor concentrations. Copyright 2006 by the American Geophysical Union.

Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space

[1] For the period 1996–2006, global distributions of tropospheric nitrogen dioxide (NO2) have been derived from radiances measured with the satellite instruments GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). A statistical analysis is applied to derive trends and seasonal variability for this period on a global scale. The time series of the monthly NO2 columns for these ten years have been fitted with a linear function superposed on an annual seasonal cycle on a grid with a spatial resolution of 1 by 1 .W e see significant reductions (up to 7% per year) in NO2 in Europe and parts of the eastern United States, and a strong increase in Asia, most particularly in China (up to 29% per year) but also in Iran and Russia. By comparing the data with the cloud information derived from the same satellite observations, the contribution of lightning to the total column of NO2 is estimated. The estimated NO2 from lightning is, especially in the tropics, in good agreement with lightning flash rate observations from space. The satellite observed seasonal variability of NO2 generally correlates well with independent observations and estimates of the seasonal cycle of specific NOx sources. Source categories considered are anthropogenic (fossil fuel and biofuel), biomass burning, soil emissions and lightning. Using the characteristics of the seasonal variability of these source categories, the dominant source of NOx emissions has been identified on a global scale and on a 1 by 1 grid.

Multimodel simulations of carbon monoxide: Comparison with observations and projected near-future changes

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 worlds populated areas.

Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe

[1] The Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite spectrometer provides detailed information on the nitrogen dioxide (NO 2) content in the planetary boundary layer. NO 2 tropospheric column retrievals of SCIAMACHY and its predecessor Global Ozone Monitoring Experiment are characterized by errors of the order of 40%. We present here a new SCIAMACHY tropospheric retrieval data set for the year 2003. The cloud free satellite observations are compared to surface measurements and simulations over western Europe performed with the regional air-quality model CHIMERE. The model has a resolution of 50 km similar to the satellite observations. For these comparisons, averaging kernels are applied to the collocated model profiles to remove the dependency of the comparison on a priori NO 2 profile information used in the retrieval. The consistency of both SCIAMACHY and CHIMERE outputs over sites where surface measurements are available allows us to be confident in evaluation of the model over large areas not covered by surface observations. CHIMERE underestimates surface NO 2 concentrations for urban and suburban stations which we mainly attribute to the low representativeness of point observations. No such bias is found for rural locations. The yearly average SCIAMACHY and CHIMERE spatial NO 2 distributions show a high degree of quantitative agreement over rural and urban sites: a bias of 5% (relative to the retrievals) and a correlation coefficient of 0.87 (n = 2003). On a seasonal basis, biases are smaller than 20% and correlation coefficients are larger than 0.75. Spatial correlations between both the model and satellite columns and the European Monitoring and Evaluation Program (EMEP) emission inventory are high in summer (r = 0.74, n = 1779) and low in winter (r = 0.48, n = 1078), related to seasonal changes in lifetime and transport. On the other hand, CHIMERE and SCIAMACHY columns are mutually consistent in summer (r = 0.82) and in winter (r = 0.79). This shows that CHIMERE simulates the transport and chemical processes with a reasonable accuracy. The NO 2 columns show a high daily variability. The daily NO 2 pollution plumes observed by SCIAMACHY are often well described by CHIMERE both in extent and in location. This result demonstrates the capabilities of a satellite instrument such as SCIAMACHY to monitor the NO 2 concentrations over large areas on a daily basis. It provides evidence that present and future satellite missions, in combination with CTM and surface data, will contribute to improve quantitative air quality analyses at a continental scale. Citation: Blond, N., K. F. Boersma, H. J. Eskes, R. J. van der A, M. Van Roozendael, I. De Smedt, G. Bergametti, and R. Vautard (2007), Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe,

Assimilation of total ozone satellite measurements in a three‐dimensional tracer transport model

The optimal-interpolation data-assimilation technique is used to combine TIROS Operational Vertical Sounder total-ozone columns with the three-dimensional tracer transport model TM3. An ozone chemistry parametrization and dry deposition of ozone are added to the model to give it the ability to simulate realistic ozone profiles. Starting from a separable form of the forecast covariance matrix, the optimal interpolation equation can be rewritten into a horizontal and vertical analysis step. First, the two-dimensional ozone column measurements are analyzed using estimates for the horizontal error covariances. In the second step of the assimilation procedure the analysis increment for the column is distributed over the vertical model layers. This step depends only on a normalized vertical weight function which is equal to the vertical covariance. Three different estimates for this weight function are introduced, using either the ozone error covariance, or the ozone time variance, or the actual ozone mass to distribute column corrections in the vertical. A comparison with independent Total Ozone Mapping Spectrometer ozone observations shows a considerable improvement of the total ozone field due to assimilation. The model error growth is small, making it suitable for assimilating sparse measurements. Ozone profiles from the assimilation appear realistic and close to the ones observed by sondes. They are capable to describe dynamical features in the lower stratosphere. However, due to the absence of vertical information, the assimilation of ozone columns has only little impact on the shape of the vertical ozone profile, which is mainly determined by the transport.

The Chemical Weather

Environmental Context. Meteorological weather—temperature, pressure, wind direction—is familiar to all, and contrasts with meteorological climate in short-term (weather) versus long-term (climate) influence. From the atmospheric chemistry side, the focus has largely been on the chemical climate, the long-term mean concentrations of important trace gases and aerosols. An emerging new focus of study is the chemical weather—the tremendous short-term variability of the atmospheric chemical composition, resulting from the strong influence of meteorological variability, chemical complexity, and regionally and temporally varying emissions.

Variational Assimilation of GOME Total-Column Ozone Satellite Data in a 2D Latitude-Longitude Tracer-Transport Model

A four-dimensional data-assimilation method is described to derive synoptic ozone fields from total-column ozone satellite measurements. The ozone columns are advected by a 2D tracer-transport model, using ECMWF wind fields at a single pressure level. Special attention is paid to the modeling of the forecast error covariance and quality control. The temporal and spatial dependence of the forecast error is taken into account, resulting in a global error field at any instant in time that provides a local estimate of the accuracy of the assimilated field. The authors discuss the advantages of the 4D-variational (4D-Var) approach over sequential assimilation schemes. One of the attractive features of the 4D-Var technique is its ability to incorporate measurements at later times t . t 0 in the analysis at time t 0, in a way consistent with the time evolution as described by the model. This significantly improves the offline analyzed ozone fields.

Ozone Forecasts of the Stratospheric Polar Vortex–Splitting Event in September 2002

Abstract The Southern Hemisphere major warming event in September 2002 has led to a breakup of the vortex in the middle and higher stratosphere and to a corresponding splitting of the ozone hole. Daily 3D ozone forecasts, produced at the Royal Netherlands Meteorological Institute (KNMI) with a tracer transport and assimilation model based on the ECMWF dynamical forecasts, provided an accurate prediction of this event a week prior to the actual breakup of the vortex. The ozone forecast model contains parameterizations for gas phase and heterogeneous chemistry. Initial states for the forecast are obtained from the assimilation of near-real-time ozone data from the Global Ozone Monitoring Experiment (GOME) on European Space Agency (ESA) Remote Sensing Satellite-2 (ERS-2). In this paper, the ozone forecasts and analyses are discussed as produced before, during, and after the event. These fields are compared with ground-based Dobson, ozonesonde, and Total Ozone Mapping Spectrometer (TOMS) observations. The tot...

Antarctic Ozone Transport and Depletion in Austral Spring 2002

Abstract The ozone budget in the Antarctic region during the stratospheric warming in 2002 is studied, using ozone analyses from the Royal Netherlands Meteorological Institute (KNMI) ozone-transport and assimilation model called TM3DAM. The results show a strong poleward ozone mass flux during this event south of 45°S between about 20 and 40 hPa, which is about 5 times as large as the ozone flux in 2001 and 2000, and is dominated by eddy transport. Above 10 hPa, there exists a partially compensating equatorward ozone flux, which is dominated by the mean meridional circulation. During this event, not only the ozone column but also the ozone depletion rate in the Antarctic region, computed as a residual from the total ozone tendency and the ozone mass flux into this region, is large. The September–October integrated ozone depletion in 2002 is similar to that in 2000 and larger than that in 2001. Simulations for September 2002 with and without ozone assimilation and parameterized ozone chemistry indicate tha...

On the use of MOZAIC-IAGOS data to assess the ability of the MACC reanalysis to reproduce the distribution of ozone and CO in the UTLS over Europe

MOZAIC-IAGOS data are used to assess the ability of the MACC reanalysis (REAN) to reproduce distributions of ozone (O3) and carbon monoxide (CO), along with vertical and inter-annual variability in the upper troposphere/lower stratosphere region (UTLS) over Europe for the period 2003–2010. A control run (CNTRL, without assimilation) is compared with the MACC reanalysis (REAN, with assimilation) to assess the impact of assimilation. On average over the period, REAN underestimates ozone by 60 ppbv in the lower stratosphere (LS), whilst CO is overestimated by 20 ppbv. In the upper troposphere (UT), ozone is overestimated by 50 ppbv, while CO is partly over or underestimated by up to 20 ppbv. As expected, assimilation generally improves model results but there are some exceptions. Assimilation leads to increased CO mixing ratios in the UT which reduce the biases of the model in this region but the difference in CO mixing ratios between LS and UT has not changed and remains underestimated after assimilation. Therefore, this leads to a significant positive bias of CO in the LS after assimilation. Assimilation improves estimates of the amplitude of the seasonal cycle for both species. Additionally, the observations clearly show a general negative trend of CO in the UT which is rather well reproduced by REAN. However, REAN misses the observed inter-annual variability in summer. The O3–CO correlation in the Ex-UTLS is rather well reproduced by the CNTRL and REAN, although REAN tends to miss the lowest CO mixing ratios for the four seasons and tends to oversample the extra-tropical transition layer (ExTL region) in spring. This evaluation stresses the importance of the model gradients for a good description of the mixing in the Ex-UTLS region, which is inherently difficult to observe from satellite instruments.