Coupling population dynamics with earth system models: the POPEM model.

Precise modeling of CO2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

Is precipitation a good metric for model performance?

Precipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients amongst all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties and there are even notable differences among different reference datasets. Several additional issues have yield to sometimes question its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation, and the crucial role of highly precise and reliable satellite estimates, such as those from the core observatory of NASA's Global Precipitation Mission (GPM).

Fluid dynamics of evolving foams.

The physical properties of many multiphase systems are determined by coarsening phenomena. From raindrops to polycrystal grains and foams, the formation and stability of these systems continuously evolve towards lower-energy configurations through events such as coalescence, Ostwald ripening and drainage. Here we propose a procedure to identify and characterise key topological transformations of coarsening phenomena using a physically-based fluid dynamic framework. In situ, real-time foaming processes of a polymeric matrix reinforced with two morphologically different nanofillers, carbon nanotubes and graphene sheets were observed by synchrotron X-ray radioscopy. We obtained detailed information on the evolution of the growth patterns and coarsening events. Filled samples showed differences in both trend and speed compared with the unfilled sample. Furthermore, we found different dominating coarsening phenomena due to the wetting nature of carbon nanoparticles. Our procedure can be extended to sequences of any type of 2D projection or 3D images and to other multiphase systems.