RESUMEN
Powerful wildfires occurring in Siberia each summer emit large amounts of smoke aerosol that, according to studies of the environmental impacts of biomass burning (BB) aerosol in different regions of the world, can affect precipitation and other weather parameters and induce feedback on fires. However, the knowledge of smoke-weather interactions and fire-weather feedback in Siberia is presently limited. To advance this knowledge, we performed coupled-meteorology-chemistry simulations of aerosols and weather in a Siberian region covering taiga and tundra using the CHIMERE chemistry-transport model and the WRF meteorological model. We addressed a monthly period of July 2016 and considered several modeling scenarios in which aerosol-radiation interaction (ARI) and aerosol-cloud interaction (ACI) were taken into account jointly or separately. The simulation results were combined with emission and precipitation data retrieved from satellite observations. The joint analysis of the simulated precipitation fields and satellite-observation-based data revealed that in the taiga, the inhibiting effect of Siberian smoke on precipitation induced a significant positive feedback on BB aerosol emissions that, according to our estimates, enhanced by 27 (±7) % respective to a hypothetical situation in which smoke-weather interactions were absent. At the same time, an increase of precipitation over active fire spots due to ACI and ARI in tundra led to the formation of a negative feedback loop between fire emissions and BB smoke, resulting in a reduction of BB aerosol emissions there by 14 (±6) %. Hence, this study revealed evidence for significant feedback of smoke-induced precipitation changes on fire emissions in Siberia. Given the global importance of Siberia as a major carbon sink, this feedback needs to be studied further and accurately taken into account in projections of climate change both on regional and global scales.
RESUMEN
Ammonia (NH3) emitted into the atmosphere from agricultural sources may affect nearby sensitive ecosystems due to high dry deposition fluxes on vegetation and soil surfaces, contributing to critical load exceedances. Ammonia fluxes near sources are simulated by either short-range atmospheric models or regional models using large grid cell sizes. However, studies are missing on the comparison of the results simulated by these two types of models. This paper presents the effect of model formalism, input factors, especially grid cell size and wind speed and the choice of deposition threshold on the spatial patterns of NH3 dry deposition fluxes and deposition threshold exceedances. We used the Eulerian chemistry-transport model CHIMERE and the Gaussian plume model OPS-ST on two study domains characterised by contrasting land use. We showed that the average annual NH3 dry deposition fluxes over each whole domain are similar for both models. By contrast, NH3 dry deposition fluxes near sources are higher when simulated with OPS-ST that provides analytical solutions that can be sampled with small grid cell sizes (i.e., from 25 to 1600 m in this study), than with CHIMERE, which uses large grid cell sizes (i.e., 800 and 1600 m). As a result, the spatial patterns of deposition threshold exceedance were very different between both models. These patterns depend mainly on grid cell size, the input factors and the choice of the deposition threshold value. We show that the model formalism has a relatively small effect on the results and that the differences result mainly from the spatial resolutions to which they can be applied. Simulation results must therefore be interpreted carefully, taking into account the simulation conditions.