Distributed Sensor Network for Land-Atmpsphere Interaction Research

Urban areas are rapidly growing and are expected to be home to nearly 68% of the world's population by the year 2050. To secure a viable environment for a safe and healthy future, it is critical to design and build cities that implement a sustainable and equitable approach in resource management and are resilient to extreme natural hazards. With these needs in mind, efforts have been invested in the past decades to advance our knowledge and capability to model urban microclimates. However, urban surfaces are inherently complex, and give rise to a host of flow phenomena that still elude our complete understanding. Moreover, existing measurement technologies are unable to exactly measure the full variability of urban surfaces and related flow phenomena, which in turn profoundly hinder the predictive capability of models and our ability to interpret measurements. Recent advances in data-assimilation and uncertainty quantification techniques offer a promising pathway to address this knowledge gap, but the success of such methods hinges on the availability of high-resolution, spatially-distributed measurements of surface and flow properties. To expand our research infrastructure and enable new research aimed at advancing the current understanding of microscale processes in urban environments, we propose to purchase a network of low- and high-fidelity meteorological towers. These instruments will concurrently measure wind, temperature, relative humidity and radiation at a variable degree of accuracy. The requested system will support transformative research advances in the field of microscale landatmosphere interaction, with research activities primarily focusing on developing accurate and efficient data-assimilation and uncertainty quantification frameworks for urban microclimate modeling. Specifically, the integrated system will allow to acquire multi-fidelity airflow measurements at relatively high spatial resolution, and in doing so successfully constrain dataassimilation and uncertainty quantification frameworks. The proposed instrumentation is expected to spearhead scientific understandings and predictive modeling capabilities that will be an asset to the Army and the Department of Defense. Foremost, an accurate probabilistic characterization of surface properties and flow phenomena is critical for urban weather forecasting, which military operations routinely rely on. The ability to conduct high-resolution measurements in urban areas will also increase the accuracy of models in predicting extreme weather conditions, which consequently can be leveraged to enhance soldiersÕ ability to efficiently and safely conduct terrestrial or drone-related operations. These include, for example, regions of high winds or high/low temperatures. From a civilian perspective, research enabled by the requested instrument also has many beneficial impacts. Notably, urban dwellers will benefit from more accurate weather forecasting, which remains a difficult task in cities. Health risks associated with pollution and heat are known concerns for urban dwellers, with marginalized communities disproportionately suffering the adverse impacts of climate change.