Evaluation of altimeter undersampling in estimating global wind and wave climate using virtual observation

2020 ◽  
Author(s):  
Haoyu Jiang
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Extreme Values ◽  
Wave Climate ◽  
Altimeter Data ◽  
Global Trends ◽  
Long Duration ◽  
Long Term Trends ◽  
Along Track

<p>Altimeters can provide global long-duration observations of oceanic wind speed and wave height. However, altimeters face the undersampling problem in estimating wind and wave climate because of their sparse sampling pattern and the changing number of in-orbit satellites. In this study, the undersampling error of altimeters was studied by sampling the ERA5 oceanic wind speed and wave height data using the track information of multiplatform altimeters. Comparisons were made between the statistics (mean, 90<sup>th</sup> and 99<sup>th</sup> percentiles, and long-term trends of them) of the original ERA5 data and the gridded along-track sampling of the ERA5 data. The results show a large discrepancy with respect to the extreme values (90<sup>th</sup> and 99<sup>th</sup> percentiles). The undersampling of altimeters can lead to significant underestimations of monthly extreme values of oceanic wind speed and wave height. Meanwhile, this underestimation is alleviated with the increase of the number of in-orbit altimeters, leading to very large overestimations of long-term trends of these extreme values over the period 1985-2018. In contrast, the annual extreme values of oceanic wind speed and wave height and their long-term trends are more reliable, although slight aforementioned biases of extreme values still exist and the data from GEOSAT are not suitable for computing annual statistics. For altimeter data, the annual values are a better option to compute long-term trends than the monthly data. This study also presents a correction scheme of using model data to compensate for the wind and wave events missed by altimeter tracks. After the correction, the global trends in oceanic wind speed and wave height over 1992-2017 are recomputed using annual statistics. The results show a clear discrepancy between the trends of wind speed and wave height during this period: the wind speed increased, while the wave height decreased. However, the reason for this discrepancy is unknown at this stage.</p>

scholarly journals The Wave Climate of the Southern Ocean

2020 ◽  
Vol 50 (5) ◽  
pp. 1417-1433
Author(s):  
Ian R. Young ◽  
Emmanuel Fontaine ◽  
Qingxiang Liu ◽  
Alexander V. Babanin
Keyword(s):  
Wind Speed ◽  
Southern Ocean ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Wave Climate ◽  
Altimeter Data ◽  
Local Wind ◽  
Significant Wave ◽  
Individual Wave

AbstractThe wave climate of the Southern Ocean is investigated using a combined dataset from 33 years of altimeter data, in situ buoy measurements at five locations, and numerical wave model hindcasts. The analysis defines the seasonal variation in wind speed and significant wave height, as well as wind speed and significant wave height for a 1-in-100-year return period. The buoy data include an individual wave with a trough to crest height of 26.4 m and suggest that waves in excess of 30 m would occur in the region. The extremely long fetches, persistent westerly winds, and procession of low pressure systems that traverse the region generate wave spectra that are unique. These spectra are unimodal but with peak frequencies that propagate much faster than the local wind. This situation results in a unique energy balance in which waves at the spectra peak grow as a result of nonlinear transfer without any input from the local wind.

100-Year Return Value Estimates for Ocean Wind Speed and Significant Wave Height from the ERA-40 Data

2005 ◽  
Vol 18 (7) ◽  
pp. 1032-1048 ◽  
Author(s):  
S. Caires ◽  
A. Sterl
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Domain Of Attraction ◽  
Altimeter Data ◽  
Time Variability ◽  
Threshold Method ◽  
Significant Wave ◽  
Ocean Wind

Abstract In this article global estimates of 100-yr return values of wind speed and significant wave height are presented. These estimates are based on the ECMWF 40-yr Re-Analysis (ERA-40) data and are linearly corrected using estimates based on buoy data. This correction is supported by global Topographic Ocean Experiment (TOPEX) altimeter data estimates. The calculation of return values is based on the peaks-over-threshold method. The large amount of data used in this study provides evidence that the distributions of significant wave height and wind speed data belong to the domain of attraction of the exponential. Further, the effect of the space and time variability of significant wave height and wind speed on the prediction of their extreme values is assessed. This is done by performing detailed global extreme value analyses using different decadal subperiods of the 45-yr-long ERA-40 dataset.

Development and Application of a Global Satellite Database of Wind and Wave Conditions

2015 ◽  
Author(s):  
I. R. Young ◽  
S. Zieger ◽  
A. V. Babanin
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Extreme Values ◽  
Wave Spectrum ◽  
The United States ◽  
Wave Climate ◽  
Global Scale ◽  
Extreme Value Statistics ◽  
Data Set ◽  
Individual Calibration

Oceanographic satellites have now been in operation for almost 30 years, collecting global data on oceanic winds and waves. During this period, a variety of satellites have been operational. These include altimeters (wind speed and wave height), SSMI radiometers (wind speed), scatterometers (wind speed and direction) and Synthetic Aperture Radar, SAR (full directional wave spectrum). Data from these instruments potentially represents an invaluable resource for offshore engineering design and facilities operation. This paper describes the development of a unique database containing data from all these instruments over their full periods of operation. The paper will describe the calibration and cross-validation of all instruments. This analysis shows the limitations of individual instruments and the relative accuracies. Instruments are calibrated against a very comprehensive buoy data set from the United States, Canada, UK, France, Spain, Australia and New Zealand. The extensive buoy dataset means that it is possible to have individual calibration buoys and independent validation sites. Further validation is provided by examining cross-over points between different satellite instruments where they image the same region of ocean at the same time. The paper will also demonstrate the application of this database. These applications include the evaluation of seasonal wind and wave climate on a global scale, the determination of extreme value statistics (100 year return values) for wind speed and wave height, long term trends in wind speed and wave height and potential trends in extreme values.

Time Series Analysis of Significant Wave Height Data for Identification of Trends in the Ocean Wave Climate

2013 ◽  
Author(s):  
Erik Vanem ◽  
Sam-Erik Walker
Keyword(s):  
Time Series ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Ocean Wave ◽  
Significant Wave ◽  
Long Time ◽  
Long Term Trends ◽  
Ocean Wave Climate

Reliable return period estimates of sea state parameters such as the significant wave height is of great importance in marine structural design and ocean engineering. Hence, time series of significant wave height have been extensively studied in recent years. However, with the possibility of an ongoing change in the global climate, this might influence the ocean wave climate as well and it would be of great interest to analyze long time series to see if any long-term trends can be detected. In this paper, long time series of significant wave height stemming from the ERA-40 reanalysis project, containing 6-hourly data over a period of more than 44 years are investigated with the purpose of identifying long term trends. Different time series analysis methods are employed, i.e. seasonal ARIMA, multiple linear regression, the Theil-Sen estimator and generalized additive models, and the results are discussed. These results are then compared to previous studies; in particular results are compared to a recent study where a spatio-temporal stochastic model was applied to the same data. However, in the current analysis, the spatial dimension has been reduced and spatial minima, mean and maxima have been analysed for temporal trends. Overall, increasing trends in the wave climate have been identified by most of the modelling approaches explored in the paper, although some of the trends are not statistically significant at the 95% level. Based on the results presented in this paper, it may be argued that there is evidence of a roughening trend in the recent ocean wave climate, and more detailed analyses of individual months and seasons indicate that these trends might be mostly due to trends during the winter months.

scholarly journals Global Wind Speed and Wave Height Extremes Derived from Long-Duration Satellite Records

2018 ◽  
Vol 32 (1) ◽  
pp. 109-126 ◽  
Author(s):  
Alicia Takbash ◽  
Ian R. Young ◽  
Øyvind Breivik
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Heavy Rain ◽  
Extreme Value ◽  
Altimeter Data ◽  
Extreme Value Analysis ◽  
Validation Data ◽  
Distribution Method ◽  
Value Analysis ◽  
Long Duration

Abstract The application of extreme-value analysis to long-duration (30 year) global altimeter and radiometer datasets is considered. In contrast to previous extreme-value analyses of satellite data, the dataset is sufficiently long to enable a peaks over threshold analysis to be undertaken. When applied to altimeter data for wind speed and significant wave height, this analysis produces values consistent with buoy validation data and previous numerical model reanalysis datasets. The spatial distributions produced are also consistent with the model reanalysis data. However, the altimeter data shows much greater finescale structure for wind speed, which is consistent with known tropical cyclone activity. The greater data density provided by radiometer measurements offers the potential to address altimeter undersampling. However, issues associated with the radiometer’s inability to measure wind speed in heavy rain events appears to create an unacceptable “fair weather” bias at extreme wind speeds. This renders the radiometer data of wind speed largely unusable for the investigation of wind speed extremes. The study also clearly demonstrates the limitations of the initial distribution method for extreme-value analysis, which is heavily biased by mean conditions.

scholarly journals THE PREDICTION OF EXTREME VALUE WIND SPEEDS AND WAVE HEIGHTS FROM SATELLITE DATA

2018 ◽  
pp. 1
Author(s):  
Alicia Takbash ◽  
Ian Young
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Wave Height ◽  
Satellite Data ◽  
Extreme Values ◽  
Essential Element ◽  
Extreme Value ◽  
Ocean Engineering ◽  
Wind Speeds

The prediction of extreme value (e.g. 1 in 100 year) estimates of wind speed and wave height is an essential element of coastal and ocean engineering design. Despite decades of research on the statistics of extreme values, the consistent limitation faced by practitioners is the requirement for a long (20 plus years) dataset at the location of interest. Long term insitu buoy deployments have started to provide useful records in some geographic locations. Long term numerical model hindcasts have also proved useful. However, buoy deployments are seldom at the location of interest and the accuracy of numerical model hindcasts more than 20 years in the past is questionable. This paper will investigate the use of long-term satellite data sets of wind speed and wave height to provide global estimates of extreme values.

Modelling Long-Term Trends in Significant Wave Height and its Potential Impacts on Ship Structural Loads

2013 ◽  
Author(s):  
Erik Vanem ◽  
Elzbieta M. Bitner-Gregersen
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Ocean Wave ◽  
Future Trends ◽  
Significant Wave ◽  
Long Term Trends ◽  
Ocean Wave Climate ◽  
The Impact

This paper presents the results from a statistical model for significant wave height in space and time. In particular, various model alternatives were applied to extract long-term temporal trends towards the year 2100. Future projections of the North Atlantic ocean wave climate based on two of these alternatives are presented, i.e. an extrapolated linear trend and trends based on regression on atmospheric levels of CO2 and assuming future emission scenarios proposed by IPCC. It is further explored how such future trends can be related to the structural load calculations of ships. It will be demonstrated how the estimated future trends can be incorporated in joint environmental models to yield updated environmental contour lines that take possible changes in the ocean wave climate into account. In this way, the impact of climate change on the wave climate can be accounted for in stress and loads calculations and hence in the structural dimensioning of ships and offshore installations. The proposed approach is illustrated by an example showing the potential impact of the estimated long-term trends in the wave climate on the wave-induced structural loads of an oil tanker. Results indicate that the impact may be far from negligible, and that this may need to be considered in the future when performing loads calculations.

scholarly journals Reliability of Extreme Significant Wave Height Estimation from Satellite Altimetry and In Situ Measurements in the Coastal Zone

2020 ◽  
Vol 8 (12) ◽  
pp. 1039
Author(s):  
Ben Timmermans ◽  
Andrew G. P. Shaw ◽  
Christine Gommenginger
Keyword(s):  
Coastal Zone ◽  
Wave Height ◽  
Satellite Data ◽  
Significant Wave Height ◽  
Wave Climate ◽  
In Situ Measurements ◽  
Altimeter Data ◽  
Sea State ◽  
Significant Wave

Measurements of significant wave height from satellite altimeter missions are finding increasing application in investigations of wave climate, sea state variability and trends, in particular as the means to mitigate the general sparsity of in situ measurements. However, many questions remain over the suitability of altimeter data for the representation of extreme sea states and applications in the coastal zone. In this paper, the limitations of altimeter data to estimate coastal Hs extremes (<10 km from shore) are investigated using the European Space Agency Sea State Climate Change Initiative L2P altimeter data v1.1 product recently released. This Sea State CCI product provides near complete global coverage and a continuous record of 28 years. It is used here together with in situ data from moored wave buoys at six sites around the coast of the United States. The limitations of estimating extreme values based on satellite data are quantified and linked to several factors including the impact of data corruption nearshore, the influence of coastline morphology and local wave climate dynamics, and the spatio-temporal sampling achieved by altimeters. The factors combine to lead to considerable underestimation of estimated Hs 10-yr return levels. Sensitivity to these factors is evaluated at specific sites, leading to recommendations about the use of satellite data to estimate extremes and their temporal evolution in coastal environments.

Nonstationary Extreme-Value Predictions in the Gulf of Mexico

2007 ◽  
Author(s):  
Christos N. Stefanakos
Keyword(s):  
Time Series ◽  
Gulf Of Mexico ◽  
Wave Height ◽  
Missing Values ◽  
Extreme Value ◽  
Altimeter Data ◽  
Dependence Structure ◽  
Measured Time ◽  
Definition Of

In the present work, return periods of various level values of significant wave height in the Gulf of Mexico are given. The predictions are based on a new method for nonstationary extreme-value calculations that have recently been published. This enhanced method exploits efficiently the nonstationary modeling of wind or wave time series and a new definition of return period using the MEan Number of Upcrossings of the level value x* (MENU method). The whole procedure is applied to long-term measurements of wave height in the Gulf of Mexico. Two kinds of data have been used: long-term time series of buoy measurements, and satellite altimeter data. Measured time series are incomplete and a novel procedure for filling in of missing values is applied before proceeding with the extreme-value calculations. Results are compared with several variants of traditional methods, giving more realistic estimates than the traditional predictions. This is in accordance with the results of other methods that take also into account the dependence structure of the examined time series.

scholarly journals Wave climate in the Arkona Basin, the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (2) ◽  
pp. 287-300 ◽  
Author(s):  
T. Soomere ◽  
R. Weisse ◽  
A. Behrens
Keyword(s):  
Baltic Sea ◽  
Wave Height ◽  
Wave Model ◽  
Wave Climate ◽  
Wind Fields ◽  
The Baltic Sea ◽  
Wave Heights ◽  
The Baltic ◽  
Basic Features

Abstract. The basic features of the wave climate in the Southwestern Baltic Sea (such as the average and typical wave conditions, frequency of occurrence of different wave parameters, variations in wave heights from weekly to decadal scales) are established based on waverider measurements at the Darss Sill in 1991–2010. The measured climate is compared with two numerical simulations with the WAM wave model driven by downscaled reanalysis of wind fields for 1958–2002 and by adjusted geostrophic winds for 1970–2007. The wave climate in this region is typical for semi-enclosed basins of the Baltic Sea. The maximum wave heights are about half of those in the Baltic Proper. The maximum recorded significant wave height HS =4.46 m occurred on 3 November 1995. The wave height exhibits no long-term trend but reveals modest interannual (about 12 % of the long-term mean of 0.76 m) and substantial seasonal variation. The wave periods are mostly concentrated in a narrow range of 2.6–4 s. Their distribution is almost constant over decades. The role of remote swell is very small.

Sign in / Sign up

Export Citation Format

Share Document