RESUMO
The global oceans are considered a major sink of atmospheric carbon dioxide (CO2). Rain is known to alter the physical and chemical conditions at the sea surface, and thus influence the transfer of CO2 between the ocean and atmosphere. It can influence gas exchange through enhanced gas transfer velocity, the direct export of carbon from the atmosphere to the ocean, by altering the sea skin temperature, and through surface layer dilution. However, to date, very few studies quantifying these effects on global net sea-air fluxes exist. Here, we include terms for the enhanced gas transfer velocity and the direct export of carbon in calculations of the global net sea-air fluxes, using a 7-year time series of monthly global climate quality satellite remote sensing observations, model and in-situ data. The use of a non-linear relationship between the effects of rain and wind significantly reduces the estimated impact of rain-induced surface turbulence on the rate of sea-air gas transfer, when compared to a linear relationship. Nevertheless, globally, the rain enhanced gas transfer and rain induced direct export increase the estimated annual oceanic integrated net sink of CO2 by up to 6%. Regionally, the variations can be larger, with rain increasing the estimated annual net sink in the Pacific Ocean by up to 15% and altering monthly net flux by > ± 50%. Based on these analyses, the impacts of rain should be included in the uncertainty analysis of studies that estimate net sea-air fluxes of CO2 as the rain can have a considerable impact, dependent upon the region and timescale.
RESUMO
This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding 'scheme blocks' framework was used to build the application ('app'), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing-a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for 'UAV toolkit' (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).
