Comparative evaluation of interpolation methods for the directivity of musical instruments

Measurements of the directivity of acoustic sound sources must be interpolated in almost all cases, either for spatial upsampling to higher resolution representations of the data, for spatial resampling to another sampling grid, or for use in simulations of sound propagation. The performance of different interpolation techniques applied to sparsely sampled directivity measurements depends on the sampling grid used but also on the radiation pattern of the sources themselves. Therefore, we evaluated three established approaches for interpolation from a low-resolution sampling grid using high-resolution measurements of a representative sample of musical instruments as a reference. The smallest global error on average occurs for thin plate pseudo-spline interpolation. For interpolation based on spherical harmonics (SH) decomposition, the SH order and the spatial sampling scheme applied have a strong and difficult to predict influence on the quality of the interpolation. The piece-wise linear, spherical triangular interpolation provides almost as good results as the first-order spline approach, albeit with on average 20 times higher computational effort. Therefore, for spatial interpolation of sparsely sampled directivity measurements of musical instruments, the thin plate pseudo-spline method applied to absolute-valued data is recommended and, if necessary, a subsequent modeling of the phase.

Revisiting global satellite observations of stratospheric cirrus clouds

As knowledge about the cirrus clouds in the lower stratosphere is limited, reliable long-term measurements are needed to assess their characteristics, radiative impact and important role in upper troposphere and lower stratosphere (UTLS) chemistry. We used 6 years (2006–2012) of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements to investigate the global and seasonal distribution of stratospheric cirrus clouds and compared the MIPAS results with results derived from the latest version (V4.x) of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data. For the identification of stratospheric cirrus clouds, precise information on both the cloud top height (CTH) and the tropopause height is crucial. Here, we used lapse rate tropopause heights estimated from the ERA-Interim global reanalysis. Considering the uncertainties of the tropopause heights and the vertical sampling grid, we define CTHs more than 0.5 km above the tropopause as stratospheric for CALIPSO data. For MIPAS data, we took into account the coarser vertical sampling grid and the broad field of view so that we considered cirrus CTHs detected more than 0.75 km above the tropopause as stratospheric. Further sensitivity tests were conducted to rule out sampling artefacts in MIPAS data. The global distribution of stratospheric cirrus clouds was derived from night-time measurements because of the higher detection sensitivity of CALIPSO. In both data sets, MIPAS and CALIPSO, the stratospheric cirrus cloud occurrence frequencies are significantly higher in the tropics than in the extra-tropics. Tropical hotspots of stratospheric cirrus clouds associated with deep convection are located over equatorial Africa, South and Southeast Asia, the western Pacific, and South America. Stratospheric cirrus clouds were more often detected in December–February (15 %) than June–August (8 %) in the tropics (±20∘). At northern and southern middle latitudes (40–60∘), MIPAS observed about twice as many stratospheric cirrus clouds (occurrence frequencies of 4 %–5 % for MIPAS rather than about 2 % for CALIPSO). We attribute more frequent observations of stratospheric cirrus clouds with MIPAS to the higher detection sensitivity of the instrument to optically thin clouds. In contrast to the difference between daytime and night-time occurrence frequencies of stratospheric cirrus clouds by a factor of about 2 in zonal means in the tropics (4 % and 10 %, respectively) and at middle latitudes for CALIPSO data, there is little diurnal cycle in MIPAS data, in which the difference of occurrence frequencies in the tropics is about 1 percentage point in zonal mean and about 0.5 percentage point at middle latitudes. The difference between CALIPSO day and night measurements can also be attributed to their differences in detection sensitivity. Future work should focus on better understanding the origin of the stratospheric cirrus clouds and their impact on radiative forcing and climate.

Quantifying Spray Deposition from a UAV Configured for Spot Spray Applications to Individual Plants

HighlightsSpot spraying is a method for applying pesticides to individual tree crowns.A new method is presented to quantify and analyze the two-dimensional spot spray deposit pattern produced by a UAV.A bivariate normal distribution provided a good fit to the observed deposition data for all treatments.Model parameters effectively described the shape of the ground deposits.Abstract. The purpose of this study was to develop a method for quantifying and analyzing the two-dimensional spray deposit pattern produced from a UAV spot spraying system for applying pesticides to individual plants with crown diameters in the range of 1 to 2 m. An XAG P20 UAV was flown over the center of a sampling grid, and spray deposits from three droplet size treatments, with nominal volume median diameters (VMDs) of 335, 430, and 1150 µm, were measured using horizontal steel plate collectors placed on blocks on the ground. A colorimetric tracer in the spray mix was used to quantify spray deposition. The positioning accuracy of the UAV was excellent, but the droplet sizes produced were much larger than expected. A bivariate normal distribution provided a good fit to the observed deposition data for all treatments. Model parameters effectively described the shape of the ground deposits. Displacement of the deposit distribution center was in a downwind direction. While there were no statistically significant effects of wind speed on the shape or degree of displacement of the center of mass of the observed ground deposit pattern, this was probably a result of the low wind speeds during the study, which were often close to or below the lower sensitivity threshold of the anemometer used. The actual spray coverage on a 2 m tall artificial tree target of 1 or 2 m diameter placed in the center of the plot was consistent across the range of droplet sizes and operating conditions tested. Nevertheless, it is hypothesized that targeting could be further improved if the UAV was slightly offset in an upwind direction and, conceptually, the degree of this displacement would increase as wind speed increased. A sampling grid spacing of 1.0 m would have produced results similar to the 0.5 m spacing actually used. Keywords: Aerial spraying, Pesticides, Spot spraying, Spray deposition, UAV, Unmanned aerial vehicle.

MACHINE TRAFFIC AND SOIL PENETRATION RESISTANCE IN GUAVA TREE ORCHARDS

ABSTRACT The study was conducted in irrigated commercial orchards of ‘Paluma’ and ‘Pedro Sato’ guavas, which were mapped with a Garmin GPS unit (Cx60). Sixty five sampling points were marked on a 21 x 21 m sampling grid. Gravimetric humidity and soil penetration resistance (SPR) were evaluated with the help of an automated penetrometer rod with a type 3 cone at a 45º angle (maximum SPR 15,100 kPa). Data with non-normal distribution were analyzed by geostatistics and interpolation by ordinary kriging. SPR values were higher where machine traffic occurs than on the lines where the crop is planted. There was spatial variability of the SPR among the layers evaluated, with the layer between 0.10-0.20 m, on the line of the machine traffic, presenting a higher SPR (>4000 kPa).

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient.