3 research outputs found
Early warning system of natural hazards and decrease of climat impact from aviation; ALARM funded project
Aviation safety can be jeopardised by multiple hazards
arising from natural phenomena, e.g., severe weather, aerosols/gases from natural hazard, and space weather. Furthermore, there are the anthropogenic emissions and climate impact of aviation that could be reduced. To mitigate such risk and/or to decrease climate impact, tactical decision-making processes could be enhanced through the development of multihazard monitoring and Early Warning System (EWS). With this objective in mind, ALARM consortium has implemented alert products (i.e., observations, detection and data access in near realtime) and tailored product (notifications, flight level — FL contamination, risk area, and visualization of emission/risk level) related to Natural Airborne Hazard (NAH, i.e., volcanic, dust and smoke clouds) and environmental hotspots. New selective detection, nowcasting and forecasts of such risks for aviation have been implemented as part of ALARM prototype EWS. This system has two functionalities. One is to provide alerts on a global coverage using remote sensing from satellites and models (focus on NAH, space weather activity and environmental hotspots). A second focuses on detecting severe weather and exceptional SO2 conditions around a selection of few airports, on providing nowcasts and forecasts of risk conditions
Quantifying the effect of mixing on the mean Age of Air in CCMVal-2 and CCMI-1 models
The stratospheric age of air (AoA) is a useful
measure of the overall capabilities of a general circulation
model (GCM) to simulate stratospheric transport. Previous
studies have reported a large spread in the simulation
of AoA by GCMs and coupled chemistry–climate models
(CCMs). Compared to observational estimates, simulated
AoA is mostly too low. Here we attempt to untangle
the processes that lead to the AoA differences between
the models and between models and observations. AoA
is influenced by both mean transport by the residual circulation
and two-way mixing; we quantify the effects of
these processes using data from the CCM inter-comparison
projects CCMVal-2 (Chemistry–Climate Model Validation
Activity 2) and CCMI-1 (Chemistry–Climate Model Initiative,
phase 1). Transport along the residual circulation is
measured by the residual circulation transit time (RCTT).
We interpret the difference between AoA and RCTT as additional
aging by mixing. Aging by mixing thus includes mixing
on both the resolved and subgrid scale. We find that the
spread in AoA between the models is primarily caused by
differences in the effects of mixing and only to some extent
by differences in residual circulation strength. These effects
are quantified by the mixing efficiency, a measure of the relative
increase in AoA by mixing. The mixing efficiency varies
strongly between the models from 0.24 to 1.02. We show
that the mixing efficiency is not only controlled by horizontal
mixing, but by vertical mixing and vertical diffusion as well.
Possible causes for the differences in the models’ mixing efficiencies
are discussed. Differences in subgrid-scale mixing
(including differences in advection schemes and model resolutions)
likely contribute to the differences in mixing efficiency.
However, differences in the relative contribution of
resolved versus parameterized wave forcing do not appear to
be related to differences in mixing efficiency or AoA