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where L00,k and L12,k are calculated at sounding station k at 0000 and 1200 UTC respectively. If more than two sounding readings were available on a given day, they would all be used in equation (18) by adding their corresponding Lh,k and dividing by the total number of profiles used; if only one sounding profile was available, only one was used. Whether the expression in equation (18) is an accurate approximation of equation (17) cannot be established a priori, as it depends on several factors, including the diurnal variation of V10, the representativeness of the profiles at 0000 and 1200 UTC, and the time zone of each station. Observations from the KSC two-level towers were therefore used to elucidate this problem.

[47] For the 15 two-level towers, the closest five surrounding sounding stations were identified (Figure 13) and LS parameters, calculated at 0000 and 1200 UTC each day, were applied to daily averages VR via equation (18). Results are summarized in Table 8. The application of the Steps 2 and 3 of the LS methodology, in combination with equation (18), produced good estimates of the average wind speed at the output height (16 m); at all towers, such estimates were also conservative. The average error was an underestimate of —19.8%, the worst case was —50.3% (tower 0001), and the best case was tower 0403 (—0.7%). The towers where the LS methodology performed worst (but still conservatively) were 0001, 0108, 0714, and 0303; the common factor among them was a large shear between the reference and the output wind speeds (i.e., p = VOBS/VREF), varying between 2.2 and 2.9. Since, from Section 2, p <3 was a restriction imposed in the LS methodology, it is expected that such towers exhibit a larger underestimate.

[48] In summary, from the KSC tower data, an analogy can be made between sounding stations and four-level towers and another between surface stations and two-level towers. It appeared that the LS methodology performed best for sounding stations (Step 1), as the average error at four-level towers was very small (—3.3%) and negative, indicative of a conservative approach. When applied to surface stations (Steps 2 and 3), LS results were poorer (but still conservative), as the average error at two-level towers was — 19.8%. Several causes can be invoked, including the distance between sounding and surface stations (Step 3), the approximation introduced by using daily averages (equation (18) instead of equation (17)), the low elevation of the ''reference height'' (~4 m), and the time zone of Florida (—5 from UTC), where soundings are retrieved during the diurnal/nocturnal transition. Further investigations are necessary to evaluate this. In any case, it appears that the approximation in equation (18) leads to satisfactory results.

3.2.3. Further Remarks

[49] The overall (i.e., sounding and surface stations) percent of class >3 stations was 12.7% (Table 1) for

Figure 10. Wind speed observed worldwide in the lowest 300 m, calculated V80 obtained with: Z0S (triangle), z0 = 0.01 (cross), a = 1/7 (square), and profile obtained (a) with the global average zJjS = 0.63 (solid line) during the day and (b) with zJjS = 0.81 at night.

the world, and ~17% for the U.S. The latter is lower than what was found previously by Archer and Jacobson [2004] (22%), due to the more conservative assumptions introduced here. In fact, KSC data show that the revised LS methodology introduced in this study may underestimate 80-m wind speeds by 3-20% (Tables 7 and 8).

[50] The results of this study can be considered conservative for the following reasons. First, a comparison with the KSC tower data showed that the LS methodology gave accurate and conservative results, for both four- and two-level towers. Even though the area covered was relatively small (Figure 13), the KSC dataset included a large number of towers and its data were quality-checked prior to their

Figure 11. Wind speed observed worldwide in the lowest 300 m, calculated V80 obtained with: a

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Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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