DOI: 10.1175/JCLI-D-12-00787.1
Scopus记录号: 2-s2.0-84877830028
论文题名: Objective determination of feature resolution in two sea surface temperature analyses
作者: Reynolds R.W. ; Chelton D.B. ; Roberts-Jones J. ; Martin M.J. ; Menemenlis D. ; Merchant C.J.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 8 起始页码: 2514
结束页码: 2533
语种: 英语
Scopus关键词: Cross-spectral analysis
; Feature resolution
; High-resolution datum
; Infrared satellites
; Microwave satellite data
; Resolution capability
; Sea surface temperature (SST)
; Small-scale features
; Computer simulation
; Oceanography
; Spectrum analysis
; Atmospheric temperature
; accuracy assessment
; error analysis
; modeling
; sea surface temperature
; spatial resolution
; spectral analysis
英文摘要: Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated "true"SST data and subsampled based on actual infrared and microwave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly 1/20°) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious smallscale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (~5 km) infrared satellite data are limited because of cloud cover. © 2013 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51891
Appears in Collections: 气候变化事实与影响
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作者单位: Cooperative Institute for Climate and Satellites, North Carolina State University, NOAA/National Climatic Data Center, Asheville, NC, United States; College of Oceanic and Atmospheric Sciences, Cooperative Institute for Oceanographic Satellite Studies, Oregon State University, Corvallis, OR, United States; Met Office, Exeter, United Kingdom; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; University of Edinburgh, Edinburgh, United Kingdom
Recommended Citation:
Reynolds R.W.,Chelton D.B.,Roberts-Jones J.,et al. Objective determination of feature resolution in two sea surface temperature analyses[J]. Journal of Climate,2013-01-01,26(8)