An air-sea partially coupled data assimilation and prediction system Xu Li

1. An air-sea partially coupled data assimilation and prediction system Xu Li Acknowledgements: John Derber, MoorthiShrinivas, Russ Treadon, Fanglin Yang, Diane Stokes, SST Group, David Behringer, IlyaRivin, Carlos Lozano, Dennis Keyser, Jeff Whiting, XingrenWu, Sarah Lu, Hua-Lu Pan. IMSG at NOAA EMC/NCEP/NOAA Abstract • An air-sea partially coupled data assimilation and prediction system has been developed within the NCEP GFS. The 6-hourly cycling runs have shown the improved SST and atmospheric analysis, the better use of observations, and neutral to positive weather forecasting impact. The near surface air temperature prediction is degraded slightly, due to the larger predicted SST RMS, which is expected to be removed/reduced through a fully coupled data assimilation and prediction system. Better diurnal warming simulation More effective use of in situ data The warming pattern simulated by the two models are very close, and DTM-1p show the larger maximum, which is closer to that of the retrievals. The decay is more natural in DTM-1p as well. The O-B statistics shows the analysis with the new scheme is better in terms of bias, rms, the number of used data and the Gaussin distribution Ocean • The ocean here is only the Near-Surface Sea Temperature (NSST): • Foundation temperature, the temperature at the base ( )of the warming layer: • Diurnal warming profile: • Sub-layer cooling profile: • SST for air-sea flux calculation in forecasting: • T-Profile down to a few mini-meters for satellite radiance simulation in analysis: SST critical in satellite data QC Improved FCST in tropics FCST impact on the RMS horizontal distribution Steady Tf degrades the FCST Partially Coupled • Partially Coupled Data assimilation:The analysis increments of both the atmosphere and ocean (foundation temperature is the only oceanic analysis variable) are generated by minimizing a single cost function but the covariance between the two media is not included • Partially Coupled Prediction: The air-sea interaction is introduced into the prediction but the SST variability is only resolved partially since foundation temperature is steady Improved FCST for T & Windin tropics. Most of the green area (smaller RMS in EXP) go through the statistics test with 95% confidence. The larger SST FCST RMS in EXP due to the introduction of the SST diurnal variability (new) leads to the slightly degradation of near surface air temperature. The error in  error in radiance simulation  reject good satellite data  biased, non-Gaussin histogram The more realistic SST evolution with a fully coupled system, in which the foundation temperature can be predicted by an OGCM, should improve the predictive skill. The horizontal distribution of the new scheme impact on the 5-day FCST. The diurnal variability of SST analysis is shown as well. Positive impact of NSSTM on FCST Discussion • The original objective of this project was to use the satellite data more effectively by assimilating radiance directly for oceanic (SST) analysis. The resolving of the oceanic diurnal variability, and air-sea interaction were added later as the kind of project upgrade. All the three new elements have enhanced the NCEP GFS and led to a partially coupled data assimilation and prediction system, which is ready for implementation technically. • The plan is to develop a fully coupled data assimilation and prediction system to get evolving foundation temperature. The covariance between atmosphere and ocean can be resolved by extending Hybrid EnKF to include the oceanic analysis variables. Scientific Basis • More consistent initialization of air-sea system by the coupled data assimilation • More realistic ocean evolution by the coupled prediction • 3. More observations used: All the observations available in GSI of NCEP GFS plus AVHRR, AMSRE and in situ sea temperature (buoys, ships…) • 4. More effective information extraction from the indirect observations (both satellite and conventional) by direct assimilation with the observation operators and their Jacobi’s • 5. Oceanic diurnal variation resolved by the 6-hourly analysis and the NSST model Improved tropics FCST for T & Wind