Mosaic image of the artificial light produced by Berlin on the night of September 11, 2010 observed from an altitude of 10,000 ft

Aerial observations of light pollution can fill an important gap between ground based surveys and nighttime satellite data. Terrestrially bound surveys are labor intensive and are generally limited to a small spatial extent, and while existing satellite data cover the whole world, they are limited to coarse resolution. This paper describes the production of a high resolution (1 m) mosaic image of the city of Berlin, Germany at night. The dataset is spatially analyzed to identify themajor sources of light pollution in the city based on urban land use data. An area-independent 'brightness factor' is introduced that allows direct comparison of the light emission from differently sized land use classes, and the percentage area with values above average brightness is calculated for each class. Using this methodology, lighting associated with streets has been found to be the dominant source of zenith directed light pollution (31.6%), although other land use classes have much higher average brightness. These results are compared with other urban light pollution quantification studies. The minimum resolution required for an analysis of this type is found to be near 10 m. Future applications of high resolution datasets such as this one could include: studies of the efficacy of light pollution mitigation measures, improved light pollution simulations, economic and energy use, the relationship between artificial light and ecological parameters (e.g. circadian rhythm, fitness, mate selection, species distributions, migration barriers and seasonal behavior), or the management of nightscapes. To encourage further scientific inquiry, the mosaic data is freely available at Pangaea.

Heat index at 2 m above ground: A globally gridded dataset based on reanalysis data from 1979-2013, links to GeoTIFFs

The increase in global mean temperatures resulting from climate change has wide reaching consequences for the earth's ecosystems and other natural systems. Many studies have been devoted to evaluating the distribution and effects of these changes. We go a step further and evaluate global changes to the heat index, a measure of temperature as perceived by humans. Heat index, which is computed from temperature and relative humidity, is more important than temperature for the health of humans and other animals. Even in cases where the heat index does not reach dangerous levels from a health perspective, it has been shown to be an important factor in worker productivity and thus in economic productivity. We compute heat index from dewpoint temperature and absolute temperature 2 m above ground from the ERA-Interim reanalysis dataset for the years 1979-2013. The data is provided aggregated to daily minima, means and maxima. Furthermore, the data is temporally aggregated to monthly and yearly values and spatially aggregated to the level of countries after being weighted by population density in order to demonstrate its usefulness for the analysis of its impact on human health and productivity. The resulting data deliver insights into the spatiotemporal development of near-ground heat index during the course of the past 3 decades. It is shown that the impact of changing heat index is unevenly distributed through space and time, affecting some areas differently than others. The likelihood of dangerous heat index events has increased globally. Also, heat index climate groups that would formerly be expected closer to the tropics have spread latitudinally to include areas closer to the poles. The data can serve in future studies as a basis for evaluating and understanding the evolution of heat index in the course of climate change, as well as its impact on human health and productivity.