Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data

Abstract

[1] This paper describes development and validation of a global climatology of basic wave parameters based on the voluntary observing ship (VOS) data from the Comprehensive Ocean-Atmosphere Data Set collection. Climatology covers the period 1958-1997 and presents heights and periods for the wind sea, swell, and significant wave height (SWH) over the global ocean on 2°Â 2°spatial resolution. Significant wave height has been derived from separate sea and swell estimates by taking square root of the sum of squares for the seas and swells propagating approximately in the same direction and assuming SWH to be equal to the higher of the two components in all other cases. Special algorithms of corrections were applied to minimize some biases, inherent in visual wave data. Particularly, we corrected overestimation of small seas, corrected underestimation of periods, and analyzed separation between sea and swell. Validation included estimation of random observational errors, observation of sampling errors, and comparison with the alternative wave data. Estimates of random observational errors show that for the majority of locations, observational uncertainties are within 20% of mean values, which allows us to discuss quantitatively the produced climatology. Biases associated with inadequate sampling were quantified using the data from high-resolution WAM hindcast for the period 1979-1993. The highest sampling biases are observed in the South Ocean, where wave height may be underestimated by 1-1.5 m because of poor sampling, primarily associated with a fair weather bias of ship routing and observation. Comparison to the other VOS-based products shows in general higher SWH in our climatology, especially in the midlatitudes. However, comparison with the altimeter data shows that even for well-sampled regions, high waves are still underestimated in VOS, suggesting a ubiquitous fair weather bias. Further ways of improving VOS-based wave climatologies and possible applications are discussed.

Recent Change—Sea Level and Wind Waves

“…Visually observed wave heights generally agree well with significant wave heights, whereas the visually estimated wave period is, on average, a few tenths of a second shorter than the peak period from hindcast simulations Hasse 1998, 1999). In contrast to offshore ship-based wave observations for estimates of wave climate (Gulev and Hasse 1999;Gulev et al 2003), use of observations from coastal sites is more problematic. On the one hand, such data pose intrinsic quality and interpretation problems, have a poor temporal resolution, contain a large element of subjectivity and a substantial amount of noise (Zaitseva-Pärnaste et al 2009), and only partially characterise the open sea wave fields (Soomere 2005).…”

“…Global, including Baltic Sea (observations from ships) No Gulev et al (2003) 1970No Gulev et al (2005 Danish waters (Drogden, multiple locations of lightships) 1931-1994-Sparre (1982 Swedish waters (multiple locations and lightships) 1965-1972No Wahl (1974 Lithuanian waters ( 1978-1996No Blomgren et al (2001 Entrance to Warnemünde harbour 1956-1993(single storms) 1988-1993No Gayer et al (1995 Pomeranian Bay No Paplińska (1999 Suursaar (2010Suursaar ( , 2013, Suursaar et al (2010Suursaar et al ( , 2012 …”

Intercomparison of global cloud cover fields over oceans from the VOS observations and NCEP/NCAR reanalysis

“…In order to produce the regular fields we used the modified method of local procedures (Akima, 1970) along with spatial smoothing with 2-dimensional Lancoz filtering (Duchon, 1979). These are exactly the algorithms used by Gulev et al (2003Gulev et al ( , 2007a for the other marine meteorological variables and fluxes. This is a common procedure for the development of global climatologies of the VOS individual variables and fluxes.…”

“…The NCEP-NCAR 6-h cloud cover was also used in our study to generate the VOS-like sampled reanalysis data set. For this purpose, we used the methodology earlier suggested by Gulev et al (2003Gulev et al ( , 2007. In order to simulate the VOS-like sampling, 6-h cloud data from reanalysis were matched to the dates and UTC hours of the ICOADS reports.…”

Periodicity and patterns of ocean wind and wave climate

“…High-quality wind and wave observations in excess of 20 years are available for climate research. These include voluntary observations along shipping routes [Gulev et al, 2003], point measurements at buoys [e.g., Bromirski et al, 2005;Menendez et al, 2008;Gemmrich et al, 2011], and spatial patterns from altimeters [e.g., Young, 1999;Woolf et al, 2002;Chen et al, 2002;Hemer et al, 2010;Young et al, 2011]. Some of these studies supplemented the measurements with detailed wave data from numerical models to provide space-time connections of the observed processes.…”