Also the IASNFS predicted salinity in the LCE is lower then the CTD measurement near the surface (024, 025 and 026). It is likely due to the inaccurate surface salinity flux applied by the IASNFS. The IASNFS uses the MODAS salinity analysis to estimate the surface salinity flux. The MODAS surface salinity shows no trace of the LCE or LC at the time. The analysis basically shows the seasonal (summer) climatology with fresh surface water covering entire northern part of the GOM. As a result, an unrealistic large surface fresh water flux was applied over the LCE and the IASNFS near surface salinity in the LCE became lower then the CTD measurement.

      The IASNFS temperatures in the GOM ambient water, including those on the shelf, compare well to the CTD (for example, 029, 035, 036, 037, 039 and 041). The IASNFS salinities, however, are in general fresher then the CTD data near the surface. It may be the result of applying an unrealistic surface salinity flux from MODAS as discussed. But it may in part due to the seasonal climatological river runoff used in IASNFS. If the Year 2003 is a dry season then the average river runoff will be unrealistically large at the summer and the near surface salinity during the time becomes too fresh.

      There are a few profiles in the GOM ambient water from IASNFS that are not consistent with the CTD data. For example, profiles 028, 032, 034 and 042 show that the IASNFS predictions have a lower temperature then the CTD data below 50-100 m. This is due to that the profiles are located in a cyclonic (cold) eddy predicted by the IASNFS. This eddy, however, may not exist or locate at the right place. The IASNFS salinity in these profiles seems to be consistent with temperature. Both temperature and salinity were upwelled due to the cyclonic motion. Unlike the temperature below 50-100 m, the near surface temperatures compare very well with CTD in those profiles. It may be due to the application of a vertical weighting function that is very weak at the upper layer in assimilating the MODAS profiles. The predicted near surface temperature, therefore, is more of a reflection of the surface heat flux and the MCSST assimilation. The weighting function works well in this case. On the other hand, the profiles 019 and 030 show that the IASNFS sometimes does not predict the surface mixed layer deep enough compared to the CTD data. It is very likely caused by the unrealistic fresh surface water which stabilize the water column and prevent mixing under the summertime light wind condition. Another group of profiles, 036, 037, 038, 039 and 040, indicate an anticyclonic warm eddy near the Texas coast. The IASNFS temperatures match well with the CTD data except at the profile 040. It suggests that this anticyclonic eddy was predicted by the IASNFS but its frontal location might not be predicted precisely.

      From the evaluation, it suggests that the altimeter data which IASNFS assimilated are sufficient to resolve the larger scale features such as the LC/LCE but may not have enough spatial/temporal resolution to precisely resolve the LC/LCE frontal location and the smaller cyclonic/anticyclonic eddies which evolve rapidly. The lost of some altimeter data, caused by GFO turnoff for example, will further degrade the prediction.

      The MODAS temperature analysis is fairly good in the region. The surface forcings from the NOGAPS and the MCSST are accurate and the model near suface temperature responds reasonably well to the forcings. The MODAS salinity analysis, however, is not consistent with temperature in the LC/LCE. At the surface, MODAS salinity analysis fails. The surface salinity flux applied to IASNFS is badly estimated from the MODAS analysis. The estimation of surface salinity flux may be improved by using the evaporation/precipitation if the reliable data are available. Also the MODAS analyses may be improved if a vertical correlation is applied. The seasonal river runoff is not sufficient for the synoptic prediction. The real-time river runoff should be used.