Cutoff Latitudes of Solar Proton Events Measured by GPS Satellites

Solar energetic particles (SEPs), one of the main causes of particle radiation in interplanetary space, can disrupt radio communication, induce spacecraft failures and change the heating and cooling rates in the atmosphere among others. To investigate the impact of SEPs and more specifically solar proton events (SPEs), we established a cutoff latitude database based on energetic particle data from Combined X-ray Dosimeters (CXDs) on board the Global Positioning System (GPS) spacecraft. Introducing a novel normalization method involving proton fluxes from the Geostationary Operational Environmental Satellites enabled us to include the CXD data from its introduction (2001) onwards. The database contains 5714 cutoff latitudes divided over six energies between 18 and 115 MeV which occur during 58 SPEs from 2001 to 2015. Based on the database, a cutoff latitude parameterization as a function of solar wind dynamic pressure and geomagnetic indices Kp and Dst is created for each energy. Moreover, comparisons to previous studies on energetic particle data from the Polar Orbiting Environmental Satellites have been performed to put the GPS data into perspective. A 1–2° poleward offset is found for the GPS based cutoff latitude models, for which several causes are discussed. Furthermore, the limitation of GPS data to geomagnetic latitudes above 60° should be considered. All in all, the usage of the long time span of GPS data in this study combined with its recent release (2016) opens up a new range of studies involving GPS energetic particle data such as investigating long-term trends with respect to our solar cycle or magnetospheric trends.publishedVersio

How Many Reindeer? UAV Surveys as an Alternative to Helicopter or Ground Surveys for Estimating Population Abundance in Open Landscapes

Conservation of wildlife depends on precise and unbiased knowledge on the abundance and distribution of species. It is challenging to choose appropriate methods to obtain a sufficiently high detectability and spatial coverage matching the species characteristics and spatiotemporal use of the landscape. In remote regions, such as in the Arctic, monitoring efforts are often resource-intensive and there is a need for cheap and precise alternative methods. Here, we compare an uncrewed aerial vehicle (UAV; quadcopter) pilot survey of the non-gregarious Svalbard reindeer to traditional population abundance surveys from ground and helicopter to investigate whether UAVs can be an efficient alternative technology. We found that the UAV survey underestimated reindeer abundance compared to the traditional abundance surveys when used at management relevant spatial scales. Observer variation in reindeer detection on UAV imagery was influenced by the RGB greenness index and mean blue channel. In future studies, we suggest testing long-range fixed-wing UAVs to increase the sample size of reindeer and area coverage and incorporate detection probability in animal density models from UAV imagery. In addition, we encourage focus on more efficient post-processing techniques, including automatic animal object identification with machine learning and analytical methods that account for uncertainties

Cutoff Latitudes of Solar Proton Events Measured by GPS Satellites

Solar energetic particles (SEPs), one of the main causes of particle radiation in interplanetary space, can disrupt radio communication, induce spacecraft failures and change the heating and cooling rates in the atmosphere among others. To investigate the impact of SEPs and more specifically solar proton events (SPEs), we established a cutoff latitude database based on energetic particle data from Combined X-ray Dosimeters (CXDs) on board the Global Positioning System (GPS) spacecraft. Introducing a novel normalization method involving proton fluxes from the Geostationary Operational Environmental Satellites enabled us to include the CXD data from its introduction (2001) onwards. The database contains 5714 cutoff latitudes divided over six energies between 18 and 115 MeV which occur during 58 SPEs from 2001 to 2015. Based on the database, a cutoff latitude parameterization as a function of solar wind dynamic pressure and geomagnetic indices Kp and Dst is created for each energy. Moreover, comparisons to previous studies on energetic particle data from the Polar Orbiting Environmental Satellites have been performed to put the GPS data into perspective. A 1–2° poleward offset is found for the GPS based cutoff latitude models, for which several causes are discussed. Furthermore, the limitation of GPS data to geomagnetic latitudes above 60° should be considered. All in all, the usage of the long time span of GPS data in this study combined with its recent release (2016) opens up a new range of studies involving GPS energetic particle data such as investigating long-term trends with respect to our solar cycle or magnetospheric trends

How Many Reindeer? UAV Surveys as an Alternative to Helicopter or Ground Surveys for Estimating Population Abundance in Open Landscapes

Conservation of wildlife depends on precise and unbiased knowledge on the abundance and distribution of species. It is challenging to choose appropriate methods to obtain a sufficiently high detectability and spatial coverage matching the species characteristics and spatiotemporal use of the landscape. In remote regions, such as in the Arctic, monitoring efforts are often resource-intensive and there is a need for cheap and precise alternative methods. Here, we compare an uncrewed aerial vehicle (UAV; quadcopter) pilot survey of the non-gregarious Svalbard reindeer to traditional population abundance surveys from ground and helicopter to investigate whether UAVs can be an efficient alternative technology. We found that the UAV survey underestimated reindeer abundance compared to the traditional abundance surveys when used at management relevant spatial scales. Observer variation in reindeer detection on UAV imagery was influenced by the RGB greenness index and mean blue channel. In future studies, we suggest testing long-range fixed-wing UAVs to increase the sample size of reindeer and area coverage and incorporate detection probability in animal density models from UAV imagery. In addition, we encourage focus on more efficient post-processing techniques, including automatic animal object identification with machine learning and analytical methods that account for uncertainties