Error estimation of buoy, satellite, and model wave height data

被引：0

作者：

Janssen, Peter A.E.M. ^{[1
]}

Abdalla, Saleh ^{[1
]}

Hersbach, Hans ^{[1
]}

Bidlot, Jean-Raymond ^{[1
]}

机构：

[1] ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom

来源：

Journal of Atmospheric and Oceanic Technology | 2007年 / 24卷 / 09期

关键词：

Triple collocation is a powerful method to estimate the rms error in each of three collocated datasets; provided the errors are not correlated. Wave height analyses from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) wave forecasting system over a 4-yr period are compared with independent buoy data and dependent European Remote Sensing Satellite-2 (ERS-2) altimeter wave height data; which have been used in the wave analysis. To apply the triple-collocation method; a fourth; independent dataset is obtained from a wave model hindcast without assimilation of altimeter wave observations. The seasonal dependence of the respective errors is discussed and; while in agreement with the properties of the analysis scheme; the wave height analysis is found to have the smallest error. In this comparison the altimeter wave height data have been obtained from an average over N individual observations. By comparing model wave height with the altimeter superobservations for different values of N; alternative estimates of altimeter and model error are obtained. There is only agreement with the estimates from the triple collocation when the correlation between individual altimeter observations is taken into account. The collocation method is also applied to estimate the error in Environmental Satellite (ENVISAT); ERS-2; altimeter; buoy; model first-guess; and analyzed wave heights. It is shown that there is a high correlation between ENVISAT and ERS-2 wave height error; while the quality of ENVISAT altimeter wave height is high. © 2007 American Meteorological Society;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Journal article (JA)

引用

页码：1665 / 1677

共 50 条

[31] Reconstruction of significant wave height distribution from sparse buoy data by using deep learning
Duan, Wenyang
Zhang, Lu
Cao, Debin
Sun, Xuehai
Zhang, Xinyuan
Huang, Limin
COASTAL ENGINEERING, 2024, 194
[32] Optimal interpolation of buoy data into a deterministic wind-wave model
Sannasiraj, S. A.
Goldstein, M. G.
NATURAL HAZARDS, 2009, 49 (02) : 261 - 274
[33] Electromagnetic bias estimates based on TOPEX, buoy, and wave model data
Kumar, R
Stammer, D
Melville, WK
Janssen, P
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2003, 108 (C11)
[34] Probability distribution of wind speed and wave height in Nowshahr Port using the data acquired from wave scan buoy
Dehghan, Yaser
Sadrinasab, Masoud
Chegini, Vahid
OCEAN ENGINEERING, 2022, 252
[35] ERROR ANALYSIS OF CROP ACREAGE ESTIMATION USING SATELLITE DATA
CHHIKARA, RS
TECHNOMETRICS, 1986, 28 (01) : 73 - 80
[36] Data fusion of significant wave height from multiple satellite altimeters
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, China
Proc SPIE Int Soc Opt Eng,
[37] Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea
A.R.Zamani
M.A.Badri
China Ocean Engineering, 2015, 29 (02) : 275 - 286
[38] Wave energy estimation by using a statistical analysis and wave buoy data near the southern Caspian Sea
Zamani, A. R.
Badri, M. A.
CHINA OCEAN ENGINEERING, 2015, 29 (02) : 275 - 286
[39] Wave energy estimation by using a statistical analysis and wave buoy data near the southern Caspian Sea
A. R. Zamani
M. A. Badri
China Ocean Engineering, 2015, 29 : 275 - 286
[40] Operational wave forecasting for extreme conditions in the Arabian Sea-A comparison with buoy and satellite data
Kazeminezhad, Mohammad Hossein
Ghavanini, Farrokh Alavian
OCEAN ENGINEERING, 2023, 275

← 1 2 3 4 5 →