Joint Calibration of Multiplatform Altimeter Measurements of Wind Speed and Wave Height over the Past 20 Years

2009 ◽  
Vol 26 (12) ◽  
pp. 2549-2564 ◽  
Author(s):  
S. Zieger ◽  
J. Vinoth ◽  
I. R. Young
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Extended Period ◽  
Cross Sectional ◽  
Significant Wave ◽  
Global Coverage ◽  
Ocean Topography ◽  
Buoy Data

Abstract Since 1985, for a period of more than 23 yr, seven altimeter missions have provided global coverage of significant wave height and wind speed. This study undertakes a long-term analysis of the accuracy and stability of altimeter-derived values of significant wave height and wind speed from the following satellites: European Remote Sensing-1 (ERS-1), ERS-2, Environmental Satellite (Envisat), Geosat, Geosat Follow-On (GFO), Jason-1, and the Ocean Topography Experiment (TOPEX). This study is a necessary step in developing a quality-controlled and fully calibrated and validated dataset from the combined satellites. Calibration of all altimeters is performed against National Oceanographic Data Center (NODC) buoy data over the extended period. These calibrations are validated using intercomparisons between satellite missions at crossover ground points. This analysis shows that, for a number of the satellites, small “step like” changes occur during the missions. These inconsistencies are removed by subdividing these missions and undertaking a partial calibration for each section of the mission. The analysis also highlights that care is necessary when attempting to apply relationships between radar cross section and wind speed derived for one altimeter to other platforms. Before undertaking such steps, it is first necessary to apply a platform-specific radar cross-sectional offset to the data.

Statistical Uncertainty in Long-Term Distributions of Significant Wave Height

1996 ◽  
Vol 118 (4) ◽  
pp. 284-291 ◽  
Author(s):  
C. Guedes Soares ◽  
A. C. Henriques
Keyword(s):  
Probability Distribution ◽  
Wave Height ◽  
Significant Wave Height ◽  
Data Sets ◽  
Monthly Basis ◽  
Significant Wave ◽  
Fitting Procedure ◽  
The One ◽  
Homogeneous Data

This work examines some aspects involved in the estimation of the parameters of the probability distribution of significant wave height, in particular the homogeneity of the data sets and the statistical methods of fitting a distribution to data. More homogeneous data sets are organized by collecting the data on a monthly basis and by separating the simple sea states from the combined ones. A three-parameter Weibull distribution is fitted to the data. The parameters of the fitted distribution are estimated by the methods of maximum likelihood, of regression, and of the moments. The uncertainty involved in estimating the probability distribution with the three methods is compared with the one that results from using more homogeneous data sets, and it is concluded that the uncertainty involved in the fitting procedure can be more significant unless the method of moments is not considered.

scholarly journals Long-Term and Seasonal Trends in Global Wave Height Extremes Derived from ERA-5 Reanalysis Data

2020 ◽  
Vol 8 (12) ◽  
pp. 1015
Author(s):  
Alicia Takbash ◽  
Ian R. Young
Keyword(s):  
Southern Hemisphere ◽  
Wave Height ◽  
Significant Wave Height ◽  
Reanalysis Data ◽  
Extreme Value Analysis ◽  
Winter Storms ◽  
Value Analysis ◽  
Weather Forecasts ◽  
Significant Wave

A non-stationary extreme value analysis of 41 years (1979–2019) of global ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis) significant wave height data is undertaken to investigate trends in the values of 100-year significant wave height, Hs100. The analysis shows that there has been a statistically significant increase in the value of Hs100 over large regions of the Southern Hemisphere. There have also been smaller decreases in Hs100 in the Northern Hemisphere, although the related trends are generally not statistically significant. The increases in the Southern Hemisphere are a result of an increase in either the frequency or intensity of winter storms, particularly in the Southern Ocean.

scholarly journals ON LONG-TERM STATISTICS FOR OCEAN AND COASTAL WAVES

1978 ◽  
Vol 1 (16) ◽  
pp. 2 ◽  
Author(s):  
Michel K. Ochi
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Contingency Table ◽  
Statistical Properties ◽  
Significant Wave ◽  
Coastal Waves ◽  
Normal Probability ◽  
Log Normal ◽  
Confidence Domain

This paper discusses the statistical properties of long-term ocean and coastal waves derived from analysis of available data. It was found from the results of the analysis that the statistical properties of wave height and period obey the bi-variate log-normal probability law. The method to determine the confidence domain for a specified confidence coefficient is presented so that reliable information in severe seas where data are always sparse can be obtained from a contingency table. Estimation of the extreme significant wave height expected in the long-term is also discussed.

scholarly journals Wind Wave Growth at Short Fetch

2008 ◽  
Vol 38 (7) ◽  
pp. 1597-1606 ◽  
Author(s):  
T. Lamont-Smith ◽  
T. Waseda
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Field Data ◽  
Wind Wave ◽  
Wind Waves ◽  
Retention Rates ◽  
Horizontal Distance ◽  
Wave Tank ◽  
Significant Wave

Abstract Wave wire data from the large wind wave tank of the Ocean Engineering Laboratory at the University of California, Santa Barbara, are analyzed, and comparisons are made with published data collected in four other wave tanks. The behavior of wind waves at various fetches (7–80 m) is very similar to the behavior observed in the other tanks. When the nondimensional frequency F* or nondimensional significant wave height H* is plotted against nondimensional fetch x*, a large scatter in the data points is found. Multivariate regression to the dimensional parameters shows that significant wave height Hsig is a function of U2x and frequency F is a function of U1.25x, where U is the wind speed and x is the horizontal distance, with the result that in general for wind waves at a particular fetch in a wave tank, approximately speaking, the wave frequency is inversely proportional to the square root of the wind speed and the wavelength is proportional to the wind speed. Similarly, the wave height is proportional to U1.5 and the orbital velocity is proportional to U. Comparison with field data indicates a transition from this fetch law to the conventional one [the Joint North Sea Wave Project (JONSWAP)] for longer fetch. Despite differences in the fetch relationship for the wave tank and the field data, the wave height and wave period satisfy Toba’s 3/2 power law. This law imposes a strong constraint on the evolution of wind wave energy and frequency; consequently, the energy and momentum retention rate are not independent. Both retention rates grow with wind speed and fetch at the short fetches present in the wave tank. The observed retention rates are completely different from those typically observed in the field, but the same constraint (Toba’s 3/2 law) holds true.

The validation of HY-2 altimeter measurements of a significant wave height based on buoy data

2013 ◽  
Vol 32 (11) ◽  
pp. 87-90 ◽  
Author(s):  
Jichao Wang ◽  
Jie Zhang ◽  
Jungang Yang
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Buoy Data

Uncertainty of Ocean Wave Hindcasts Due to Wind Modeling

1995 ◽  
Vol 117 (4) ◽  
pp. 294-297 ◽  
Author(s):  
J. C. Teixeira ◽  
M. P. Abreu ◽  
C. Guedes Soares
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Height ◽  
Significant Wave Height ◽  
Second Generation ◽  
Wave Model ◽  
Ocean Wave ◽  
Wind Fields ◽  
Significant Wave ◽  
Wind Input

Two wind models were developed and their results were compared with data gathered during the Wangara experiment, so as to characterize their uncertainty. One of the models was adopted to generate the wind fields used as input to a second generation wave model. The relative error in the wind speed was considered in order to assess the uncertainties of the predictions or the significant wave height. Different time steps for the wind input were also used to determine their effect on the predicted significant wave height.

scholarly journals Projected sea level rise and changes in extreme storm surge and wave events during the 21st century in the region of Singapore

2015 ◽  
Vol 12 (6) ◽  
pp. 2955-3001
Author(s):  
H. Cannaby ◽  
M. D. Palmer ◽  
T. Howard ◽  
L. Bricheno ◽  
D. Calvert ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Wave Height ◽  
21St Century ◽  
Significant Wave Height ◽  
Quantitative Assessment ◽  
Climate Model ◽  
Mean Sea Level ◽  
Significant Wave

Abstract. Singapore is an island state with considerable population, industries, commerce and transport located in coastal areas at elevations less than 2 m making it vulnerable to sea-level rise. Mitigation against future inundation events requires a quantitative assessment of risk. To address this need, regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events have been combined to explore potential changes to coastal flood risk over the 21st century. Local changes in time mean sea level were evaluated using the process-based climate model data and methods presented in the IPCC AR5. Regional surge and wave solutions extending from 1980 to 2100 were generated using ~ 12 km resolution surge (Nucleus for European Modelling of the Ocean – NEMO) and wave (WaveWatchIII) models. Ocean simulations were forced by output from a selection of four downscaled (~ 12 km resolution) atmospheric models, forced at the lateral boundaries by global climate model simulations generated for the IPCC AR5. Long-term trends in skew surge and significant wave height were then assessed using a generalised extreme value model, fit to the largest modelled events each year. An additional atmospheric solution downscaled from the ERA-Interim global reanalysis was used to force historical ocean model simulations extending from 1980–2010, enabling a quantitative assessment of model skill. Simulated historical sea surface height and significant wave height time series were compared to tide gauge data and satellite altimetry data respectively. Central estimates of the long-term mean sea level rise at Singapore by 2100 were projected to be 0.52 m (0.74 m) under the RCP 4.5 (8.5) scenarios respectively. Trends in surge and significant wave height 2 year return levels were found to be statistically insignificant and/or physically very small under the more severe RCP8.5 scenario. We conclude that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century. We note that the largest recorded surge residual in the Singapore Strait of ~ 84 cm lies between the central and upper estimates of sea level rise by 2100, highlighting the vulnerability of the region.

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