Atmospheric water balance and trend over ocean estimated from satellite, merged and reanalysis data

Thursday, 18 December 2014
Dong-Bin Shin and Hyo-Jin Park, Yonsei University, Seoul, South Korea
The column integrated atmospheric water balance over the ocean was examined using satellite-based and merged datasets for the period from 2000 to 2007. The datasets for the components of the atmospheric water balance include evaporation from the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data (HOAPS), the Japanese Ocean Flux Data sets with Use of Remote Sensing Observations (J-OFURO2) and the Objectively Analyzed Air-Sea Heat Fluxes (OAFlux) and precipitation from the HOAPS, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Global Precipitation Climatology Project (GPCP). The water vapor tendency was derived from water vapor data of HOAPS. The product for water vapor flux convergence estimated using satellite observation data was used. The atmospheric balance components from the Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis data were also examined. Residuals of the atmospheric water balance equation were estimated using nine possible combinations of the datasets over the ocean between 60°N and 60°S.

The results showed that there was considerable disagreement in the residual intensities and distributions from the different combinations of the datasets. In particular, the residuals in the estimations of the satellite-based atmospheric budget appear to be large over the oceanic areas with heavy precipitation such as the intertropical convergence zone, South Pacific convergence zone, and monsoon regions. The lack of closure of the atmospheric water cycle may be attributed to the uncertainties in the datasets and approximations in the atmospheric water balance equation. Meanwhile, the anomalies of the residuals from the nine combinations of the datasets are in good agreement with their variability patterns. These results suggest that significant consideration is needed when applying the datasets of water budget components to quantitative water budget studies, while climate variability analysis based on the residuals may produce similar results. The linear trends of the residuals were also obtained by least-squares regression with statistical significance levels. The regional characteristics of the trends will be also discussed.