A new methodology for the estimation of smoke-injection height from wild-land fires is proposed and evaluated. It is demonstrated that the approaches developed for estimating the plume rise from stacks, such as the formulas of G. Briggs, can be formally written in terms characterising the wild-land fires: fire energy, size and temperature. However, these semi-empirical methods still perform quite poorly because the physical processes controlling the uplift of the wildfire plumes differ from those controlling the plume rise from stacks. The proposed new methodology considers wildfire plumes in a way similar to Convective Available Potential Energy (CAPE) computations. The new formulations are applied to a dataset collected within the MISR Plume Height Project for about 2000 fire plumes in North America and Siberia. The estimates of the new method are compared with remote-sensing observations of the plume top by the MISR instrument, with two versions of the Briggs' plume-rise formulas, with the 1-D plume-rise model BUOYANT, and with the prescribed plume-top position (the approach widely used in dispersion modelling). The new method has performed significantly better than all these approaches. For two-thirds of the cases, its predictions deviated from the MISR observations by less than 500 m, which is the uncertainty of the observations themselves. It is shown that the fraction of "good" predictions is much higher (>80%) for the plumes reaching the free troposphere.

This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM_2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4–5.5.2006, 15.8–25.8.2006 and in August 2008). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available ground-based observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM_2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate non-linear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is expected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire-originated concentrations of aerosols (PM_2.5, PM₁₀, sulphates and nitrates) and AOD, as predicted by the SILAM model were mainly within a factor of 2–3 compared with the observations. The main challenges of the FAS improvement include refining of the emission factors globally, determination of the types of fires (smouldering vs flaming), evaluation of the injection heights of the plumes, and predicting the temporal evolution of fires.

The problem of characteristic vertical profile of smoke released from wildland fires is considered. A methodology for bottom-up evaluation of this profile is suggested and a corresponding global dataset is calculated. The profile estimation is based on: (i) a semi-empirical formula for plume-top height recently suggested by the authors, (ii) satellite observations of active wildland fires, and (iii) meteorological conditions evaluated for each fire using output of the numerical weather prediction model. Injection profiles of the plumes from all fires recorded globally from March 2000 till November 2012 are estimated with a time step of 1 h. The resulting 4-dimensional dataset is split into daytime and nighttime subsets. The subsets are projected onto a global grid with a resolution of 1° × 1° × 500 m, aggregated to a monthly level, and normalised by total emissions in each vertical column. Evaluation of the obtained dataset was performed in several ways. Firstly, the quality of the semi-empirical formula for plume-top computations was evaluated using updated MISR fire Plume Height Project data. Secondly, the upper percentiles of the profiles are compared with an independent dataset of space lidar CALIOP. Thirdly, the results are compared with the distribution suggested for AEROCOM modelling community. Finally, the inter-annual variations of the calculated profiles are estimated.

The impact of the El Niño Southern Oscillation (ENSO) on the Northern Hemisphere mid-winter zonal wind, temperature, and stationary planetary waves (SPWs) is evaluated using the Middle and Upper Atmosphere Model and Modern-Era Retrospective Analysis for Research and Applications (MERRA). The composites determined using simulated ensembles and MERRA winters with different ENSO phases show that the mean zonal wind in the stratosphere at higher-middle latitudes is weaker and polar region is warmer, and the activity of SPW1 is higher during El Niño events. The simulated and observed SPW2 amplitude behaves in the opposite way, and it is stronger in the stratosphere during La Niña. The observed changes of SPW1 and SPW2 amplitudes under La Niña and El Niño events should affect an efficiency of the stratosphere–troposphere coupling in different longitudinal sectors through the changes in horizontal distributions of the downward wave activity flux.