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Remote Sensing

Characterization of offshore wind-energy patterns

NASA's QuikSCAT satellite maps the global wind characteristics over the oceans to achieve optimal deployment of wind farms and to understand weather and climate changes.
8 October 2008, SPIE Newsroom. DOI: 10.1117/2.1200809.1274

Sailors understand both the importance of and the difficulty in getting information on wind speed, direction, and variability over the oceans. Just a few decades ago almost all ocean-wind measurements were obtained by merchant ships, often resulting in nonuniform data quality and geographical distribution. Today, operational ‘numerical weather prediction’ also yields wind information. However, this approach depends on computational models that are intrinsically limited by our knowledge of the relevant physical processes and the availability of the requisite data. The importance of accurate wind measurements is clearly emphasized, for example, when a hurricane suddenly intensifies and changes course or when the unexpected delay of monsoon brings drought.

With increasing demands for electric power and the need to reduce greenhouse-gas emissions, turning wind energy into electric power has never been more important. New technology has enabled floating wind farms in the open seas to capture the greater offshore wind energy and reduce the environmental impact on coastal regions. Access to a representative map of the readily available wind energy would help optimize wind-farm deployment.

Surface winds vary significantly, both geographically and temporally. Adequate coverage of their distribution and characteristics can only be achieved from space. Microwave scatterometers are the most suitable instruments developed to measure the wind-stress magnitude and wind direction under both clear and cloudy conditions, night and day.1 Scatterometers send microwave pulses to the earth's surface and measure the backscattered power. The oceans' surface roughness is largely due to small centimeter waves which are roughly in equilibrium with the local stress (defined as the momentum exchange generated by vertical wind shear and buoyancy). Stress drives ocean currents. These devices are unique in measuring both the stress magnitude and direction.

Figure 1. Wind-power distribution measured by NASA's QuikSCAT satellite for (a) boreal winter (December–January–February: DJF) and (b) summer (June–July–August: JJA), computed from the wind-speed probability distribution for the eight-year period from 2000 to 2007 (color scale in units of W m2). The gray scale shows the land topography.

Over the large expanse of the ocean the atmospheric stratification is near-neutral, and any current is negligibly small compared with the wind speed. Thus, the measured backscatter power and surface stress can be used to represent the actual wind. The surface-stress variability is quite different from that of the wind at locations where strong ocean-current shear and temperature gradients are present in ocean fronts (such as the Agulhas2 and Kuroshio Extensions3) and where strong hurricane-like winds dominate. Under such conditions a scatterometer provides the only large-scale stress measurements.

We computed the probability distributions of the wind speed and the wind-power density over global oceans using eight years of NASA's QuikSCAT measurements.4 They trace the variation and higher-order moments which are critical to assess the nonlinear effects of wind on electric-power-generation capability, shipping hazards, and air–sea exchanges in heat, water, and greenhouse gases. The resulting power-density distribution confirms our general knowledge of atmospheric circulation as regards mid-latitude storm tracks, trade winds, and monsoons (see Figure 1). It also exhibits regions of high wind power associated with flow distortion by land, wind channeled by land topography, and buoyancy effects on turbulent stress driven by ocean fronts. We examined the subdaily power-density variation using wind stress from two identical scatterometers flying in tandem for six months.5

One polar-orbiting scatterometer in a low-altitude (∼800km) orbit can only sample a given location on Earth twice daily. Additional instruments flying in tandem allow studies of higher temporal variability and reduction of the aliasing signal (the bias introduced by subsampled measurements) of the mean wind stress. A future constellation of scatterometers flown by the United States, Europe, India, and China may provide six-hourly coverage.5 Potential improvements of future generations of these devices include higher spatial resolution, better wind-direction selection, lower rain contamination, and increased detection capacity of both stronger and weaker winds.

This study was carried out at the Jet Propulsion Laboratory of the California Institute of Technology with joint support from NASA's oceanvector wind and physical-oceanography programs.

W. Timothy Liu
Jet Propulsion Laboratory
Pasadena, CA

W. Timothy Liu is a senior research scientist. He was previously leader of the air–sea interaction and climate team (1989–2005) and project scientist of a series of NASA satellite projects (1992–2006). He is a fellow of both the American Meteorological Society and the American Association for the Advancement of Science.