In favorable atmospheric conditions, fires can produce pyrocumulonimbus cloud (pyroCb) in the form of deep convective columns resembling conventional thunderstorms, which may be accompanied by strong inflow, dangerous downbursts, and lightning strikes that can produce dangerous changes in fire behavior. PyroCb formation conditions are not well understood and are difficult to forecast. This paper presents a theoretical study of the thermodynamics of fire plumes to better understand the influence of a range of factors on plume condensation. Plume gases are considered to be undiluted at the fire source and approach 100% dilution at the plume top (neutral buoyancy). Plume condensation height changes are considered for this full range of dilution and for a given set of factors that include environmental temperature and humidity, fire temperature, and fire-moisture-to-heat ratios. The condensation heights are calculated and plotted as saturation point (SP) curves on thermodynamic diagrams. The position and slope of the SP curves provide insight into how plume condensation is affected by the environment thermodynamics and ratios of fire heat to moisture production. Plume temperature traces from large-eddy model simulations added to the diagrams provide additional insight into plume condensation heights and plume buoyancy at condensation. SP curves added to a mixed layer lifting condensation level on standard thermodynamic diagrams can be used to identify the minimum plume condensation height and buoyancy required for deep, moist, free convection to develop, which will aid pyroCb prediction.

Wheat rust diseases pose one of the greatest threats to global food security, including subsistence farmers in Ethiopia. The fungal spores transmitting wheat rust are dispersed by wind and can remain infectious after dispersal over long distances. The emergence of new strains of wheat rust has exacerbated the risks of severe crop loss. We describe the construction and deployment of a near realtime early warning system (EWS) for two major wind-dispersed diseases of wheat crops in Ethiopia that combines existing environmental research infrastructures, newly developed tools and scientific expertise across multiple organisations in Ethiopia and the UK. The EWS encompasses a sophisticated framework that integrates field and mobile phone surveillance data, spore dispersal and disease environmental suitability forecasting, as well as communication to policy-makers, advisors and smallholder farmers. The system involves daily automated data flow between two continents during the wheat season in Ethiopia. The framework utilises expertise and environmental research infrastructures from within the cross-disciplinary spectrum of biology, agronomy, meteorology, computer science and telecommunications. The EWS successfully provided timely information to assist policy makers formulate decisions about allocation of limited stock of fungicide during the 2017 and 2018 wheat seasons. Wheat rust alerts and advisories were sent by short message service and reports to 10 000 development agents and approximately 275 000 smallholder farmers in Ethiopia who rely on wheat for subsistence and livelihood security. The framework represents one of the first advanced crop disease EWSs implemented in a developing country. It provides policy-makers, extension agents and farmers with timely, actionable information on priority diseases affecting a staple food crop. The framework together with the underpinning technologies are transferable to forecast wheat rusts in other regions and can be readily adapted for other wind-dispersed pests and disease of major agricultural crops.

Spotting can start fires up to tens of kilometres ahead of the primary fire front, causing rapid spread and placing immense pressure on suppression resources. Here, we investigate the dynamics of the buoyant plume generated by the fire and its ability to transport firebrands. We couple large-eddy simulations of bushfire plumes with a firebrand transport model to assess the effects of turbulent plume dynamics on firebrand trajectories. We show that plume dynamics have a marked effect on the maximum spotting distance and determine the amount of lateral and longitudinal spread in firebrand landing position. In-plume turbulence causes much of this spread and can increase the maximum spotting distance by a factor of more than 2 over that in a plume without turbulence in our experiments. The substantial impact of plume dynamics on the spotting process implies that fire spread models should include parametrisations of turbulent plume dynamics to improve their accuracy and physical realism.