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Svein Vagle, William G. Large, and David M. Farmer


The potential of the WOTAN technique to estimate oceanic winds from underwater ambient sound is thoroughly evaluated. Anemometer winds and sound spectrum levels at 11 frequencies in the range 3–25 kHz from the FASINEX Experiment are used to establish both the frequency and wind speed dependencies of ambient sound. These relationships are then tested using independent data from four other deployments, and found to hold in the deep ocean in the OCEAN STORMS but not in shallow coastal waters. The OCEAN STORMS ambient-sound wind speed estimates are within ±0.5 m s−1 of anemometer values for wind speeds between 4 and 15 m s−1. Causes of differences, including disequilibrium of the surface wave field, are discussed and it is argued that they are no larger than expected.

The procedure for processing ambient-sound data is developed. It includes temperature dependent calibration detection of shipping and precipitation contamination, and standardization of measurements to 1 m depth. The latter procedure allows data from different depths and sound speed profiles to be compared. The potential for using the technique on remote platforms is assessed. On-board processing and subsequent despiking and interpolation would result in a continuous wind record. For time scales of 12 hours or longer the results would be very similar to those obtained with an anemometer. Over shorter time scales there may be some important differences.

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C. Adam Schlosser, Xiang Gao, Kenneth Strzepek, Andrei Sokolov, Chris E. Forest, Sirein Awadalla, and William Farmer


The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: specifically, the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, the authors present a technique that extends the latitudinal projections of the 2D atmospheric model of the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and this approach is demonstrated in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, the authors characterize the climate models’ spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of metaensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate model projections. This hybridization of the climate model longitudinal projections with the global and latitudinal patterns projected by the IGSM can, in principle, be applied to any given state or flux variable that has the sufficient observational and model-based information.

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