The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

[1] We present an approach for diagnosing errors in land surface models in the time and frequency domains. The approach is applied to the Community Atmosphere-BiosphereLand Exchange (CABLE). We compare modeled and observed fluxes of net ecosystem carbon exchange (NEE), latent heat (LE) and sensible heat (H) at two different forested flux station sites. Using wavelet analysis, we identify the frequencies where model errors are relatively large, and then analyze the sensitivities of model errors at those frequencies to selected model parameters, yielding significant improvements in several measures of model performance. At Harvard Forest, the predictions by CABLE using the modified parameter values reduce model errors at daily to yearly timescales for all three fluxes, but not at interannual timescales for NEE. At the Tumbarumba site, predictions by CABLE with modified parameter values reduce the variance of model errors of all three fluxes from daily to interannual timescales, but do not improve the agreement with the observed mean diurnal or daily time series for H. We conclude that analyzing both mean and variance of model errors at a range of time/frequency scales is useful for identifying and reducing errors of a land surface model.

No abstract

No abstract

Abstract. Schemes used to parameterise ozone dry deposition velocity at the oceanic surface mainly differ in terms of how the dominant term of surface resistance is parameterised. We examine three such schemes and test them in a global climate-chemistry model that incorporates meteorological nudging and monthly-varying reactive-gas emissions. The default scheme invokes the commonly used assumption that the water surface resistance is constant. The other two schemes, named the one-layer and two-layer reactivity schemes, include the simultaneous influence on the water surface resistance of ozone solubility in water, waterside molecular diffusion and turbulent transfer, and a firstorder chemical reaction of ozone with dissolved iodide. Unlike the one-layer scheme, the two-layer scheme can indirectly control the degree of interaction between chemical reaction and turbulent transfer through the specification of a surface reactive layer thickness. A comparison is made of the modelled deposition velocity dependencies on sea surface temperature (SST) and wind speed with recently reported cruise-based observations. The default scheme overestimates the observed deposition velocities by a factor of 2-4 when the chemical reaction is slow (e.g. under colder SSTs in the Southern Ocean). The default scheme has almost no temperature, wind speed, or latitudinal variations in contrast with the observations. The one-layer scheme provides noticeably better variations, but it overestimates deposition velocity by a factor of 2-3 due to an enhancement of the interaction between chemical reaction and turbulent transfer. The two-layer scheme with a surface reactive layer thickness specification of 2.5 µm, which is approximately equal to the reaction-diffusive length scale of the ozone-iodide reaction, is able to simulate the field measurements most closely with respect to absolute values as well as SST and wind-speed dependence. The annual global oceanic deposition of ozone determined using this scheme is approximately half of the original oceanic deposition obtained using the default scheme, and it corresponds to a 10 % decrease in the original estimate of the total global ozone deposition. The previously reported modelled estimate of oceanic deposition is roughly one-third of total deposition and with this new parameterisation it is reduced to 12 % of the modelled total global ozone deposition. Deposition parameterisation influences the predicted atmospheric ozone mixing ratios, especially in the Southern Hemisphere. For the latitudes 45-70 • S, the two-layer scheme improves the prediction of ozone observed at an altitude of 1 km by 7 % and that within the altitude range 1-6 km by 5 % compared to the default scheme.