The safe development paradox of the United States regulatory floodplain.

In the United States, requirements for flood insurance, development restrictions, and federal buyout program eligibility rely on regulatory designation of hazardous zones, i.e., inside or outside the 100-year floodplain.

Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk.

Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e.

Mapping Yearly Fine Resolution Global Surface Ozone through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output for 1990-2017.

Estimates of ground-level ozone concentrations are necessary to determine the human health burden of ozone. To support the Global Burden of Disease Study, we produce yearly fine resolution global surface ozone estimates from 1990 to 2017 through a data fusion of observations and models. As ozone observations are sparse in many populated regions, we use a novel combination of the MFusion and Bayesian Maximum Entropy (BME) methods.