HR: 1330h
AN: GC12A-0158    [PDF]
TI: Analysis of the Surface Radiation Budget Data in Terms of Empirical Orthogonal Functions (EOFs)
AU: * Zhang, T
EM: t.zhang@larc.nasa.gov
AF: AS \& M, One Enterprize Parkway, Suite 300, Hampton, VA 23666-5845 United States
AU: Stackhouse, P W
EM: Paul.W.Stackhouse@nasa.gov
AF: NASA Langley Research Center, 21 Langley Boulevard, Mail Stop 420, Hampton, VA 23681-2199 United States
AU: Cox, S J
EM: s.j.cox@larc.nasa.gov
AF: AS \& M, One Enterprize Parkway, Suite 300, Hampton, VA 23666-5845 United States
AU: Smith, G L
EM: g.l.smith@larc.nasa.gov
AF: NASA Langley Research Center, 21 Langley Boulevard, Mail Stop 420, Hampton, VA 23681-2199 United States
AU: Chiacchio, M
EM: m.chiacchio@larc.nasa.gov
AF: AS \& M, One Enterprize Parkway, Suite 300, Hampton, VA 23666-5845 United States
AB: The version Release 2 from the WCRP/GEWEX SRB project at the NASA Langley Research Center is a significant upgrade from the V1.1 WCRP SRB Shortwave 4-year data set. The new version has a 1-degree spatial resolution in both latitude and longitude and covers the period from July 1983 to October 1995. Meanwhile, we have acquired the field observations of shortwave radiation at about 1000 sites worldwide for the past thirty plus years. Previous analysis of seasonal variations showed that the seasonal cycles of net shortwave radiation and net total radiation can be described by first 3 EOFs so that more than 98 % of the variance is expressed. The net longwave radiation is more complex and requires many more terms. A subsequent study showed that the EOFs which express the geographical distributions could be simply related to the climate classes. In this study, we focus upon the interannual fluctuations using the monthly means of the surface shortwave radiation from the above databases, and we apply the EOFs to the analyses of both the SRB data and the surface-based observations and their differences. We show, among other things, the first few EOFs of the global surface shortwave flux and their associated principle components (PCs). The EOF whose associated PC shows significant correlation with the El Nino Southern Oscillation (ENSO) Index (SOI) epitomizes the variability of the surface shortwave flux associated with the ENSO. A geographical PC analysis will seek to identify the dominant processes determining long-term variability in the dataset.
DE: 0305 Aerosols and particles (0345, 4801)
DE: 1600 GLOBAL CHANGE (New category)
DE: 1620 Climate dynamics (3309)
DE: 1640 Remote sensing
DE: 1655 Water cycles (1836)
SC: Global Climate Change [GC]
MN: 2003 Fall Meeting