Climate change influences on agricultural research productivity

This paper investigates the impacts of climate change on US returns to research investments on agricultural productivity. We examine this using a historical data set in a panel time-series econometric model of state agricultural productivity. The fitted model allows derivation of the rate of return to research investments and the effects of climate change thereon. We find climate change is altering the rate of return to public agricultural research in a spatially heterogeneous manner. Increases in precipitation raise returns to research, while the impact of higher temperatures varies by region, are negative in Southern areas, particularly the Southern Plains, and positive in northern areas. We simulate the impact of projected climate change and find cases where agricultural productivity is reduced, for example in the Southern Plains. Finally, we consider the amount of research investment that is needed to adapt to overcome the impacts of climate change on agricultural productivity. Under the 2100 scenario, a 7–17 % increase in total US research investment is needed to adapt, but effects by region differ greatly—some requiring little changes and the Southern Plain requiring an increase as high as 57 %.     

Radar backscattering from artificially grown sea ice

Fine-resolution X-band backscatter measurements were made at the US Army Cold Region Research and Engineering Laboratory in Jan. 1987. Backscatter data were collected from unmodified smooth ice and snow-covered ice and from ice from which the snow had been removed (slightly roughened ice). The results indicate that vertically polarized returns were consistently higher than horizontally polarized echoes from both the slightly roughened and snow-covered saline ice. A 6.5-cm-thick dry snow layer altered the σ^o of the original smooth-surfaced saline ice only slightly, but introduced a noticeable volume scattering component. It is shown that although substantial agreement exists between the bare first-year ice measurements and commonly used surface-scatter model predictions, a complete model of first-year ice must include a volume-scatter contribution     

Retracking considerations in spaceborne GNSS-R altimetry

The European Space Agency Passive Reflectometry and Interferometry System In-orbit Demonstrator (IoD) aims to perform mesoscale altimetric observations by measuring the Global Navigation Satellite System (GNSS) opportunity signals reflected over the sea surface. Altimetry based on GNSS reflectometry (GNSS-R) is significantly affected by satellite motion, since it requires relatively long integration times to reduce noise. We present the impact of the satellite motion on the GNSS-R observables and the need to retrack the waveforms. By using a detailed GNSS-R space mission simulator, the change of delay difference between the direct and the reflected signals during the incoherent averaging of the waveform has been investigated. Their effects on the waveform shape and the altimetric performance are presented comparing the aligned and non-aligned waveforms. Results show that the performance of spaceborne GNSS-R altimeter is seriously degraded without a proper alignment of the waveform samples.     

Heat balance and eddies in the Peru-Chile current system

The Peru-Chile current System (PCS) is a region of persistent biases in global climate models. It has strong coastal upwelling, alongshore boundary currents, and mesoscale eddies. These oceanic phenomena provide essential heat transport to maintain a cool oceanic surface underneath the prevalent atmospheric stratus cloud deck, through a combination of mean circulation and eddy flux. We demonstrate these behaviors in a regional, quasi-equilibrium oceanic model that adequately resolves the mesoscale eddies with climatological forcing. The key result is that the atmospheric heating is large (>50 W m^?2) over a substantial strip >500 km wide off the coast of Peru, and the balancing lateral oceanic flux is much larger than provided by the offshore Ekman flux alone. The atmospheric heating is weaker and the coastally influenced strip is narrower off Chile, but again the Ekman flux is not sufficient for heat balance. The eddy contribution to the oceanic flux is substantial. Analysis of eddy properties shows strong surface temperature fronts and associated large vorticity, especially off Peru. Cyclonic eddies moderately dominate the surface layer, and anticyclonic eddies, originating from the nearshore poleward Peru-Chile Undercurrent (PCUC), dominate the subsurface, especially off Chile. The sensitivity of the PCS heat balance to equatorial intra-seasonal oscillations is found to be small. We demonstrate that forcing the regional model with a representative, coarse-resolution global reanalysis wind product has dramatic and deleterious consequences for the oceanic circulation and climate heat balance, the eddy heat flux in particular.     

Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters

Although GNSS techniques are theoretically sensitive to the Earth center of mass, it is often preferable to remove intrinsic origin and scale information from the estimated station positions since they are known to be affected by systematic errors. This is usually done by estimating the parameters of a linearized similarity transformation which relates the quasi-instantaneous frames to a long-term frame such as the International Terrestrial Reference Frame (ITRF). It is well known that non-linear station motions can partially alias into these parameters. We discuss in this paper some procedures that may allow reducing these aliasing effects in the case of the GPS techniques. The options include the use of well-distributed sub-networks for the frame transformation estimation, the use of site loading corrections, a modification of the stochastic model by downweighting heights, or the joint estimation of the low degrees of the deformation field. We confirm that the standard approach consisting of estimating the transformation over the whole network is particularly harmful for the loading signals if the network is not well distributed. Downweighting the height component, using a uniform sub-network, or estimating the deformation field perform similarly in drastically reducing the amplitude of the aliasing effect. The application of these methods to reprocessed GPS terrestrial frames permits an assessment of the level of agreement between GPS and our loading model, which is found to be about 1.5 mm WRMS in height and 0.8 mm WRMS in the horizontal at the annual frequency. Aliased loading signals are not the main source of discrepancies between loading displacement models and GPS position time series.     

Eddy formation in the bays of Kamchatka and fluxes to the open ocean

Ocean Dynamics - The Eastern Kamchatka Current (EKC) is the western boundary current of the North Pacific subpolar gyre. Southeast of the Kamchatka Peninsula lies a large anticyclonic eddy, the...     

Microlensing by cosmic strings

We consider the signature and detectability of gravitational microlensing of distant quasars by cosmic strings. Because of the simple image configuration such events will have a characteristic lightcurve, in which a source would appear to brighten by exactly a factor of 2, before reverting to its original apparent brightness. We calculate the optical depth and event rate, and conclude that current predictions and limits on the total length of strings on the sky imply optical depths of ≲ 10⁻⁸ and event rates of fewer than one event per 10⁹ sources per year. Disregarding those predictions but replacing them with limits on the density of cosmic strings from the cosmic microwave background fluctuation spectrum, leaves only a small region of parameter space (in which the sky contains about 3 × 10⁵ strings with deficit angle of the order of 0.3 milli-seconds) for which a microlensing survey of exposure 10⁷ source years, spanning a 20–40-year period, might reveal the presence of cosmic strings.     

Spectral simulation of vector random fields with stationary Gaussian increments in <Emphasis Type="Italic">d</Emphasis>-dimensional Euclidean spaces

This paper addresses the problem of simulating multivariate random fields with stationary Gaussian increments in a d-dimensional Euclidean space. To this end, one considers a spectral turning-bands algorithm, in which the simulated field is a mixture of basic random fields made of weighted cosine waves associated with random frequencies and random phases. The weights depend on the spectral density of the direct and cross variogram matrices of the desired random field for the specified frequencies. The algorithm is applied to synthetic examples corresponding to different spatial correlation models. The properties of these models and of the algorithm are discussed, highlighting its computational efficiency, accuracy and versatility.