Hurricane Katrina Winds Measured by a Buoy-Mounted Sonic Anemometer

Howden, Stephan; Gilhousen, David B.; Guinasso, Norman L.; Walpert, John N.; Sturgeon, Michael; Bender, Leslie

doi:10.1175/2007jtecho518.1

Cited by 26 publications

(16 citation statements)

References 6 publications

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“…Large et al (1995) suggest that due to flow disturbance ''wind speed decreases much faster with height in the presence of waves'' and propose corrections at high speeds. Howden et al (2008) show that Hurricane Katrina consistently tilted a moored buoy by 208 or more, causing an underestimate of about 10% in the speeds from a traditional anemometer. Underestimates of high winds would only have a minor effect on the overall buoy statistics.…”

Section: ) Buoy and Rig Windsmentioning

confidence: 94%

Factors Affecting Ship and Buoy Data Quality: A Data Assimilation Perspective

Ingleby

2010

Journal of Atmospheric and Oceanic Technology

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Ship and buoy reports of wind, air pressure, temperature, humidity, and sea temperature for 2007 and 2008 have been compared with values from the operational Met Office global numerical weather prediction (NWP) system. Ship reports have been categorized by vessel type, recruiting country, and manual or automatic reporting. Most estimated ship winds (except Dutch ones) are too strong and are better treated as measured winds. After height adjustment, the average ship wind speeds are reasonably consistent with buoy wind speeds, but the global model winds are 6%-12% weaker. Extra care is needed when comparing/assimilating values close to the coast. Ship air temperatures are too warm during the afternoon due to solar heating of the ship. Adjustment of the pressure to sea level is a problem for some larger ships. Passenger ship reports are relatively poor quality for several variables and their winds are rather strong. Automated ship reports and those from research and coast guard vessels tend to be of good quality but some of the winds are slightly too weak. In most respects buoy data have the best quality. A number of improvements to the Met Office observation processing system are being made, notably tightening of the quality checks and better height adjustment of winds.

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Section: ) Buoy and Rig Windsmentioning

confidence: 94%

Factors Affecting Ship and Buoy Data Quality: A Data Assimilation Perspective

Ingleby

2010

Journal of Atmospheric and Oceanic Technology

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“…Additional adjustments related to factors not investigated in this paper, such as buoy tilt and other buoy motions, or wave sheltering (Pond, 1968;Skey et al, 1998Skey et al, , 1999Taylor et al, 2002;Howden et al, 2008), may be needed. These adjustments may differ depending on hull type or size.…”

Section: Discussionmentioning

confidence: 99%

Buoy wind inhomogeneities related to averaging method and anemometer type: application to long time series

Thomas

Swail

2011

Intl Journal of Climatology

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Moored buoy observations began two to three decades ago. These datasets have value for calibration of remotely sensed data, validation of weather and ocean wave models, input to reanalysis models, and studies of climate trend and variability. Changes in buoy wind observation methods have the potential to introduce inhomogeneities into the time series. These include changes in anemometer height (typically between 5 and 10 m) with changes in platform type; the transition in the 1980s and 1990s from use of a vector-mean to a scalar-mean averaging method; and, in recent years, the introduction of ultrasonic anemometers in the buoy networks, as well as the continued use of mechanical propellervane type of anemometers. This study examines differences in buoy wind measurements from RM Young propeller-vane and Vaisala ultrasonic anemometers installed on the same buoy, and differences in vector-averaged and scalar-averaged wind speeds from the same RM Young anemometer. This study also considers the effect of waves on these differences. The comparisons are based on large multi-year datasets from 6-m buoys with boat-shaped hulls (6N) and 3-m buoys with round hulls (3D), deployed off the coasts of Canada in the northeast Pacific and northwest Atlantic Oceans. Results of the anemometer type comparison suggest that the Vaisala ultrasonic winds are 0.16 ms −1 + 1.6% of the RM Young winds. Results of the vector scalar comparison of Canadian buoy data show that scalar mean winds were 2.1% and 2.7% greater than RM Young vector mean winds from 6N and 3D buoys, respectively. Vector-scalar differences increased with increasing wave height, more quickly with 3D than with 6N buoys. Results are used to adjust the winds from a long-term buoy in the northeast Pacific. The height adjustment is shown to be more important than the adjustment for vector or scalar averaging of the sustained wind speed, in terms of the impact of monthly mean wind speeds. A homogeneity testing program finds other unexplained significant shifts in the time series of monthly mean wind speeds.

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“…During Hurricane Katrina, sensors from a CenGOOS buoy survived winds in excess of 280 km/h (170 mph) and transmitted a rare continuous record of meteorologic and oceanographic data as the historic storm passed. 48 Data sets such as these are tremendously valuable because they are used in hindcast models and enable progress to be made in subsequent forecasts. • GCOOS partners at the TAMU Conrad Blucher Institute have developed several specialized products using data from the TCOON, a data node partially funded by the GCOOS-RA.…”

Section: Issue: Hurricanes and Extra-tropical Storms In The Gulf Of Mmentioning

confidence: 99%