A Field Evaluation of NDBC Moored Buoy Winds

Gilhousen, David B.

doi:10.1175/1520-0426(1987)004<0094:afeonm>2.0.co;2

Cited by 125 publications

(63 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Values of ROEV for estimated ship winds were larger. Gilhousen (1987) found wind speed variances of 2.0 and 3.2 m 2 s −2 from paired buoys located about 40 and 110 km apart. Our values also compare well with equivalent values for ships of between 4.0 and 4.8 m 2 s −2 in the region of interest for U 10N (Kent and Berry, 2005).…”

Section: 'Errors-in-variables' Least-squares Regressionmentioning

confidence: 99%

“…However, significant temporal changes in the size and type of observing platform (including the introduction of moored buoys in the 1970s) and in measurement methods have introduced inhomogeneities to databases of archived marine winds. Inhomogeneities occur for many reasons, including: different observing methods (Quayle, 1980;Peterson and Hasse, 1987;Cardone et al, 1990;Wilkerson and Earle, 1990;Kent et al, 1993Kent et al, , 1998Lindau 1995a;); systematic changes in measurement height (Cardone et al, 1990); airflow distortion over the ship (Dobson, 1981;Yelland et al, 2002;Moat et al, 2005); different averaging times and methods (Dobson, 1981;Pierson, 1983;Gilhousen 1987;Taylor et al, 2002); and the effect of environmental conditions (Dobson, 1981;Kent et al, 1993). Other sources of observational error include: differences from nominal observing time; the anemometer type, calibration, and location; errors in calculation of true wind from the relative wind (Kent et al, 1993;Gulev, 1999;Smith et al, 1999); rounding artefacts; and for Beaufort winds, the stage of development of the waves.…”

Section: Introductionmentioning

confidence: 99%

“…The effect of waves, including breaking waves, on near-surface airflow (Hare et al, 1997;Janssen, 1999) and on the buoy motion (Taylor et al, 2002) can also add a bias or increase uncertainty. Buoy winds have limited spatial and temporal coverage; however, moored buoy winds have smaller random observational error than ship winds (Gilhousen, 1987;Kent and Berry, 2005). Buoys report hourly, and are considered to be more reliable for validation of numerical model and remotely sensed data (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Methods to homogenize wind speeds from ships and buoys

Thomas¹,

Kent

Swail³

2005

Intl Journal of Climatology

View full text Add to dashboard Cite

Marine winds reported by Voluntary Observing Ships (VOS) and moored buoys require adjustment to provide a homogeneous record of the marine climate. Known sources of inhomogeneity arise from differences in measurement height and method, averaging method and atmospheric stability; methods are available to correct for these. However, significant differences remain in a paired dataset of ship and buoy winds. Regression methods to remove this remaining inconsistency are discussed, and a ranked regression method chosen as most appropriate to adjust ship wind speeds to yield a similar distribution. We show the factors, such as vessel type, that affect the regression results. The corrections, derived from a high-quality paired dataset with rigorous quality control, are effective at reducing inhomogeneity in monthly mean wind speed distributions derived from the International Comprehensive Ocean-Atmosphere Data Set.

show abstract

Section: 'Errors-in-variables' Least-squares Regressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Methods to homogenize wind speeds from ships and buoys

Thomas¹,

Kent

Swail³

2005

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…This type of buoy has been widely used for wave and wind measurements (e.g. Weller et al, 1991;Gilhousen, 1987Gilhousen, , 2006, equipped with a Datawell HIPPY 40 heave-acceleration, a pitch and roll sensor, a twoaxis magnetometer, compasses, barometers, and water temperature sensors. A twin-propeller wind anemometer was mounted on the mast of the buoy 5 m above the designed waterline of the buoy hull, and the wind speed was logged at the same frequency, approximately 1.7 Hz, as the wave measurement.…”

Section: Field Observationmentioning

confidence: 99%

“…This allows for a direct comparison of the wind and wave data with the same precision. Gilhousen (1987 and2006) performed exhaustive validations for the quality of the wind measurements obtained from such a 3-m discus buoy in response to the suspicion of the possible data contamination due to the buoy's motions. The measured wind signals from a 3-m discus buoy were compared with those recorded from nearby buoys of the same kind, from stationary platforms (e.g.…”

Section: Field Observationmentioning

confidence: 99%

Long-term wave growth and its linear and nonlinear interactions with wind fluctuations

Liu

2008

Ann. Geophys.

View full text Add to dashboard Cite

Abstract.Following Ge and Liu (2007), the simultaneously recorded time series of wave elevation and wind velocity are examined for long-term (on Lavrenov's τ 4 -scale or 3 to 6 h) linear and nonlinear interactions between the wind fluctuations and the wave field. Over such long times the detected interaction patterns should reveal general characteristics for the wave growth process. The time series are divided into three episodes, each approximately 1.33 h long, to represent three sequential stages of wave growth. The classic Fourierdomain spectral and bispectral analyses are used to identify the linear and quadratic interactions between the waves and the wind fluctuations as well as between different components of the wave field.The results show clearly that as the wave field grows the linear interaction becomes enhanced and covers wider range of frequencies. Two different wave-induced components of the wind fluctuations are identified. These components, one at around 0.4 Hz and the other at around 0.15 to 0.2 Hz, are generated and supported by both linear and quadratic windwave interactions probably through the distortions of the waves to the wind field. The fact that the higher-frequency wave-induced component always stays with the equilibrium range of the wave spectrum around 0.4 Hz and the lowerfrequency one tends to move with the downshifting of the primary peak of the wave spectrum defines the partition of the primary peak and the equilibrium range of the wave spectrum, a characteristic that could not be revealed by short-time wavelet-based analyses in Ge and Liu (2007). Furthermore, these two wave-induced peaks of the wind spectrum appear to have different patterns of feedback to the wave field. The quadratic wave-wave interactions also are assessed using the auto-bispectrum and are found to be especially active during the first and the third episodes. Such directly detected wind-wave interactions, both linear and nonlinear, may comCorrespondence to: Z. Ge (ge.zhongfu@epa.gov) plement the existing theoretical and numerical models, and can be used for future model development and validation.

show abstract

A review of uncertainty in in situ measurements and data sets of sea surface temperature

2014

View full text Add to dashboard Cite

Archives of in situ sea surface temperature (SST) measurements extend back more than 160 years.Quality of the measurements is variable, and the area of the oceans they sample is limited, especially early in the record and during the two world wars. Measurements of SST and the gridded data sets that are based on them are used in many applications so understanding and estimating the uncertainties are vital. The aim of this review is to give an overview of the various components that contribute to the overall uncertainty of SST measurements made in situ and of the data sets that are derived from them. In doing so, it also aims to identify current gaps in understanding. Uncertainties arise at the level of individual measurements with both systematic and random effects and, although these have been extensively studied, refinement of the error models continues. Recent improvements have been made in the understanding of the pervasive systematic errors that affect the assessment of long-term trends and variability. However, the adjustments applied to minimize these systematic errors are uncertain and these uncertainties are higher before the 1970s and particularly large in the period surrounding the Second World War owing to a lack of reliable metadata. The uncertainties associated with the choice of statistical methods used to create globally complete SST data sets have been explored using different analysis techniques, but they do not incorporate the latest understanding of measurement errors, and they want for a fair benchmark against which their skill can be objectively assessed. These problems can be addressed by the creation of new end-to-end SST analyses and by the recovery and digitization of data and metadata from ship log books and other contemporary literature.

show abstract

A Field Evaluation of NDBC Moored Buoy Winds

Cited by 125 publications

References 0 publications

Methods to homogenize wind speeds from ships and buoys

Methods to homogenize wind speeds from ships and buoys

Long-term wave growth and its linear and nonlinear interactions with wind fluctuations

A review of uncertainty in in situ measurements and data sets of sea surface temperature

Contact Info

Product

Resources

About