Eugene J. Farrell

Measuring Aeolian Saltation: A Comparison of Sensors

Abstract We report the results of field experiments designed to compare four types of aeolian saltation sensors: the Safire; the Wenglor® Particle Counter; the Miniphone; and the Buzzer Disc. Sets of sensors were deployed in tight spatial arrays and sampled at rates as fast as 20 kHz. In two of the three trials, the data from the sensors are compared to data obtained from sand traps. The Miniphone and the Buzzer Disc, based on microphone and piezoelectric technologies, respectively, produced grain impact counts comparable to those derived from the trap data. The Safire and the Wenglor® Particle Counter produce count rates that were an order of magnitude too slow. Safires undercount because of their large momentum threshold and because its signal is saturated at relatively slow transport rates. We conclude that the Miniphone and the Buzzer Disc are appropriate for deployment as grain counters because their small size allows them to be installed in closely-spaced sets.

Dynamics of sediment storage and release on aeolian dune slip faces: A field study in Jericoacoara, Brazil

Sediment transport on the lee sides of aeolian dunes involves a combination of grain-fall deposition on the upper portion of the slip face until a critical angle is exceeded, transport of a portion of those sediments down the slip face by grain flows and, finally, deposition at an angle of repose. We measured the mean critical and repose angles and the rate of slip-face avalanching using terrestrial laser scanning (TLS) on two barchans of different size in Jericoacoara, Brazil. Wind speeds and sand fluxes were measured simultaneously at the dune crests. We found that the mean critical and repose angles decrease with increasing wind speed. We attribute this to turbulent shear stresses, the magnitude of which are predicted using 3D Large-Eddy Simulation (LES) modeling, that episodically act down the slip face (i.e. in the direction of gravity) to trigger grain flows at lower angles than with gravity stresses alone. The rate of avalanching is a maximum in the morning at our study site and coincides with the maximum rate of increase in wind speed and not with the maximum rate of sediment supply to the slip face. We developed and tested a new predictive model for the rate of avalanching that includes both sediment flux delivered to the slip face and the derivative of the critical angle with time. Our data also suggest that the mean critical angle varies inversely with slip-face height. These results have important implications for aeolian dune evolution, interpretations of aeolian stratigraphy, and granular mechanics.

A new relationship between grain size and fall (settling) velocity in air

The fall velocity of natural sand grains is a fundamental attribute of sediment transport in fluid environments where particles may become partially or fully suspended. Several formulae have been proposed to calculate the fall velocity of particles in air, but there is considerable uncertainty about which is the most accurate or appropriate for a given set of environmental conditions. Five experiments that reported observations of fall velocity of different types of particles in air are described, evaluated, and compared. The experiment data were quality-controlled using four criteria: (1) particles had to have sufficient drop heights to attain their terminal fall velocity; (2) particles had to be in the range of sand sizes; (3) data identified as being problematic by the original authors were removed; and (4) particles comprise natural, irregular shaped sediments. The quality-controlled data were aggregated and analyzed using linear regression to obtain a relationship between grain size (d, in mm) and fall velocity (w0 , in ms-1): w 0 = 4.248 d + 0.174 . This is a statistically strong relationship with a coefficient of determination of 0.89 (p < 0.001). This relationship can be regarded as a universal fall velocity model for natural, sand-sized particles falling through a static column of air. In terms of predictive analyses, our heuristic method outperforms alternative formulae and yields a better fit to the experimental data over the full range of sand sizes.

The challenges of protecting rural coastal communities from climate change impacts. A Case Study: Maharees Conservation Association CLG

The MCA for their ongoing support and selfless work. Landowners, residents, and visitors to the Maharees. EF & KL would like to thank OPW & KCC for research support. EF would like to acknowledge support of Ms Sheena Fennell and Dr Martin White (EOS NUIG). MCA Partners: KCC, NPWS, IT Tralee, NUIG, OPW, Clean Coasts, TDs.

Benchmarking the War Against Global Warming

We analyzed the HadCRUT3 reconstruction of the instrumental global temperature record for 1850 through 2008 to decompose thirty-year temperature trends into signal and noise components. The signal represents multidecadal trends and the noise represents annual variability about those trends. Historical estimates of temperature variability (e.g., noise) are used with seven temperature projections to simulate global warming time series. These trends include the 1979 through 2008 trend, four trends taken from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations (A1B, A2, B2, and the constant composition commitment [CCC] scenarios) and trends representing approaches to 1.5°C and 2°C warming by 2100. Each series is simulated 1,000 times. The results are compared, statistically, to the current warming rate of 0.016°C year−1. We calculate the time until those trends become statistically different from the trend observed over the most recent thirty-year period (1979–2008). The results indicate that it will probably be decades before distinct changes from the current warming rate become apparent. For the A1B scenario, only 25 percent of the simulations indicate difference by 2040. For the CCC, A2, 1.5°C, and 2°C scenarios, the 25 percent level is reached in about 2030, 2040, 2065, and 2075, respectively. Only about 10 percent of the B1 simulations indicate a difference before 2100. These results indicate that we should expect decades to pass before impacts of the war against global warming become apparent.