Expected Changes of Montenegrin Climate, Impact on the Establishment and Spread of the Asian Tiger Mosquito (Aedes albopictus), and Validation of the Model and Model-Based Field Sampling

Aedes albopictus has become established in many parts of Europe since its introduction at the end of the 20th century. It can vector a range of arboviruses, of which Chikungunya and Dengue are most significant for Europe. An analysis of the expected climate change and the related shift in Köppen zones for Montenegro and impact on the establishment of Ae. albopictus was conducted. Outputs of a mechanistic Aedes albopictus model were validated by 2245 presence/absence records collected from 237 different sites between 2001 and 2014. Finally, model-based sampling was designed and performed at 48 sites in 2015, in a previously unexplored northern part of Montenegro, and results were validated. The Eta Belgrade University (EBU)-Princeton Ocean Model (POM) regional climate model was used with the A2 emissions scenario for the 2001–2030 and 2071–2100 integration periods. The results point to a significant increase in suitability for the mosquito and a vertical shift to higher altitudes by the end of the century. The model showed excellent results with the area under the receiver operating characteristic curve (AUC) of 0.94. This study provides a tool for prioritizing surveillance efforts (model-based surveillance), especially when resources are limited. This is the first published analysis of Climate Change that incorporates observations from the national synoptic grid and the subsequent impact on Ae. albopictus in Montenegro.

Improving the simulation of convective dust storms in regional-to-global models

Convective dust storms have significant impacts on atmospheric conditions and air quality and are a major source of dust uplift in summertime. However, regional-to-global models generally do not accurately simulate these storms, a limitation that can be attributed to (1) using a single mean value for wind speed per grid box, i.e., not accounting for subgrid wind variability and (2) using convective parametrizations that poorly simulate cold pool outflows. This study aims to improve the simulation of convective dust storms by tackling these two issues. Specifically, we incorporate a probability distribution function for surface wind in each grid box to account for subgrid wind variability due to dry and moist convection. Furthermore, we use lightning assimilation to increase the accuracy of the convective parameterization and simulated cold pool outflows. This updated model framework is used to simulate a massive convective dust storm that hit Phoenix, AZ, on 6 July 2011. The results show that lightning assimilation provides a more realistic simulation of precipitation features, including timing and location, and the resulting cold pool outflows that generated the dust storm. When those results are combined with a dust model that accounts for subgrid wind variability, the prediction of dust uplift and concentrations are considerably improved compared to the default model results. This modeling framework could potentially improve the simulation of convective dust storms in global models, regional climate simulations, and retrospective air quality studies.