2,197 research outputs found
The mHealth Conundrum: Smartphones & Mobile Medical Apps - How Much FDA Medical Device Regulation Is Required
Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands
Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible
Sensitivity Kernels for Flows in Time-Distance Helioseismology: Extension to Spherical Geometry
We extend an existing Born approximation method for calculating the linear
sensitivity of helioseismic travel times to flows from Cartesian to spherical
geometry. This development is necessary for using the Born approximation for
inferring large-scale flows in the deep solar interior. In a first sanity
check, we compare two mode kernels from our spherical method and from an
existing Cartesian method. The horizontal and total integrals agree to within
0.3 %. As a second consistency test, we consider a uniformly rotating Sun and a
travel distance of 42 degrees. The analytical travel-time difference agrees
with the forward-modelled travel-time difference to within 2 %. In addition, we
evaluate the impact of different choices of filter functions on the kernels for
a meridional travel distance of 42 degrees. For all filters, the sensitivity is
found to be distributed over a large fraction of the convection zone. We show
that the kernels depend on the filter function employed in the data analysis
process. If modes of higher harmonic degree () are
permitted, a noisy pattern of a spatial scale corresponding to
appears near the surface. When mainly low-degree modes are used
(), the sensitivity is concentrated in the deepest regions and it
visually resembles a ray-path-like structure. Among the different low-degree
filters used, we find the kernel for phase-speed filtered measurements to be
best localized in depth.Comment: 17 pages, 5 figures, 2 tables, accepted for publication in ApJ. v2:
typo in arXiv author list correcte
- …