Evaluating the Impact of the Number of Satellite Altimeters Used in an Assimilative Ocean Prediction System
NAVAL RESEARCH LAB STENNIS SPACE CENTER MS
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The impact of the number of satellite altimeters providing sea surface height anomaly SSHA information for a data assimilation system is evaluated using two comparison frameworks and two statistical methodologies. The Naval Research Laboratory NRL Layered Ocean Model NLOM dynamically interpolates satellite SSHA track data measured from space to produce high-resolution eddy resolving fields. The Modular Ocean Data Assimilation System MODAS uses the NLOM SSHA to produce synthetic three-dimensional fields of temperature and salinity over the global ocean. A series of case studies is defined where NLOM assimilates different combinations of data streams from zero to three altimeters. The resulting NLOM SSHA fields and the MODAS synthetic profiles are evaluated relative to independently observed ocean temperature and salinity profiles for the years 2001-03. The NLOM SSHA values are compared with the difference of the observed dynamic height from the climatological dynamic height. The synthetics are compared with observations using a measure of thermocline depth. Comparisons are done point for point and for 18 radius regions that are linearly fit over 2-month periods. To evaluate the impact of data outliers, statistical evaluations are done with traditional Gaussian statistics and also with robust nonparametric statistics. Significant error reduction is obtained, particularly in high SSHA variability regions, by including at least one altimeter. Given the limitation of these methods, the overall differences between one and three altimeters are significant only in bias. Data outliers increase Gaussian statistical error and error uncertainty compared to the same computations using nonparametric statistical methods.
- Operations Research
- Unmanned Spacecraft
- Physical and Dynamic Oceanography