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The NVAP global water vapor data set: independent cross-comparison and multiyear variability

Remote Sensing of Environment
Publication Date
DOI: 10.1016/s0034-4257(00)00199-1
  • Earth Science
  • Geography


Abstract Space–time variability in the global distribution of atmospheric total column water vapor (tcwp) greatly impacts the hydrologic cycle. NASA's Water Vapor Project (NVAP) produced a global 1°×1° tcwp data set for use as a tool to investigate, among other things, atmospheric variability. An independent cross-comparison of the NVAP tcwp product was performed using the TOPEX/POSEIDON (T/P) TOPEX microwave radiometer (TMR) data and the European Centre for Medium-Range Weather Forecasts (ECMWF)-based range delay data set produced by Météo-France (MF) and distributed with T/P data. When these T/P range delay data are converted to tcwp, they show that NVAP is biased dry and ECMWF/MF is biased wet relative to the independent TMR measurement. Although the absolute accuracy of the NVAP tcwp product is uncertain, results indicate its relative accuracy is sufficient for variability studies. Empirical orthogonal function (EOF) analysis and spectral analysis applied to this data set show that seasonal variability over the annual cycle accounts for about 20% of the variance (EOF1). An El Niño-southern oscillation (ENSO) signal is found in the annually demeaned data; the magnitude of the cross-correlation between the temporal amplitude (TA) of EOF1 and the Niño 3.4 (SST) time series is .9. Comparisons also were made between the NVAP patterns of variability in tcwp and independent reanalysis and interpretation of numerical model generated atmospheric fields. In general, there is good agreement between the NVAP data and the reanalysis fields. Finally, specific recommendations are made for: (1) improvement of the NVAP data set upon reanalysis and (2) use of the NVAP data, in place of ECMWF/MF-based range delay data, for T/P retrievals when TMR data are not available if and when T/P data are reanalyzed. This latter recommendation is especially important for regions of the tropical Indo-Pacific (e.g., Indonesia) where islands can interfere with valid TMR retrievals.

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