Subseasonal Prediction with the NCEP-CFS: Forecast Skill and Prediction Barriers for Tropical Intraseasonal Oscillations

1. Subseasonal Prediction with the NCEP-CFS: Forecast Skill and Prediction Barriers for Tropical Intraseasonal Oscillations

2. Messages to take back home� The CFS is a useful tool in forecasting Tropical Intraseasonal Oscillations (TIO) which are the basis for subseasonal prediction� its skill is similar to other centers The reason for the drop in skill is found in the Maritime Continent which presents a Barrier to the eastward propagation of the active convective phase of the TIO Increasing the horizontal resolution of the atmospheric model was not sufficient to break the Maritime continent Barrier and thus to improve the skill of TIO forecast A better set of initial conditions is shown to be crucial for improving skill by 3-5 days. Both better representation of the state of the atmosphere and better compatibility of the initial conditions with the forecast model appears to be important Intraseasonal variations of oceanic initial states are not well represented by the ocean analysis (GODAS). However, ocean � atmosphere coupling is quite important for the TIO. It follows that inconsistencies between the ocean and atmospheric initial state at this portion of the spectrum may damage the forecast There are additional sources of predictability to take advantage from for subseasonal forecasting e.g., subseasonal prediction over the Sahel (Vintzileos and Thiaw, 2006)

3. The CFS

5. Subseasonal Forecasting

7. Issues concerning subseasonal forecasting: How critical are Initial Conditions? How critical is model resolution? How critical are model drifts and biases? What are the most adequate ensemble generation techniques?

9. Tropical Intraseasonal Oscillations

10. Tropical Intraseasonal Oscillations: some reminders TIO are the most important (but not unique) source of predictability for subseasonal forecasting -- they are what ENSO is to seasonal forecasting Comprehensive dynamical models do not represent them perfectly though there is consensus that coupling with the ocean improves their simulation Observations show that sometimes the MJO collapses to higher zonal modes as it crosses the Maritime Continent � this underlines the necessity for ensemble forecast

11. Forecasting Tropical Intraseasonal Oscillations with the CFS

12. Defining a metric for the TIO One of the most used metrics (Wheeler and Hendon) represents the coupling between the large scale circulation and organized diabatic forcing by combining winds at 200 hPa and 850 hPa and precipitation or OLR. In this work we show results from hindcasts from 2002 to 2006 which is a mostly quiet period in regard to ENSO events. Nevertheless, in order to avoid possible sampling issues when defining mean annual cycles and drifts we only use the smoothest possible variable for defining an index. We use zonal wind at 200 hPa averaged from 20�S-20�N (area containing the Gill solutions for a heating source on the equator).

13. Defining a metric for the TIO

17. Defining a metric for the TIO

18. Some initial experimentation with subseasonal forecasting at NCEP� We used the T126 (100 km x 100 km) version of the operational T62 CFS (200 km x 200 km) Hindcasts were run up to 65 days and were initialized four times per day (00Z, 06Z, 12Z and 18Z) from CDAS2 and GODAS from May 7th to July 15th and from November 7th to January 15th from 2000 to 2004 (run by Saha, Vintzileos, Thiaw and Johanson )

20. Reasons for the drop in skill:The Maritime Continent Barrier

23. In order to study the Maritime Continent Barrier we designed a series of subseasonal retrospective forecasts with the CFS (Proposed to and endorsed by the Climate Test Bed FY2007)

25. CDAS2 vs. GDAS Data assimilation done with older version of GFS at T62L28 (older than the GFS used in the CFS) This is a multi-year long estimation of the Atmospheric state obtained with the same, albeit older, model and same assimilation methodologies Quality is time-invariant Data assimilation done with the newest version of GFS (very similar to the one used in CFS) at T254L64 and T382L64 This is the best available estimation of the Atmospheric state obtained by the best model and assimilation techniques available each day Quality improves with time

26. Forecast skill for TIO as a function of Resolution and Initial Conditions

28. Reasons for the drop in forecast skill:The Maritime Continent Barrier

31. �and the Ocean? There is consensus that the ocean plays an important role for the evolution of the TIO CFS is initialized by GODAS which in turn is optimized for Seasonal-to-Interannual forecast GODAS: Comes in pentads Its SST is damped to the weekly Reynolds SST Contains information from 2 weeks before and two weeks after

36. Is there any relevance between the daily OI SST EOF modes and the TIO?

39. There is an empirical relationship between the SST and the TIO suggesting that initial states for the ocean and the atmosphere should be coherent

40. Impact of the drift to the forecast skill

43. Messages to take back home� The CFS is a useful tool in forecasting Tropical Intraseasonal Oscillations (TIO) which are the basis for subseasonal prediction� its skill is similar to other centers The reason for the drop in skill is found in the Maritime Continent which presents a Barrier to the eastward propagation of the active convective phase of the TIO Increasing the horizontal resolution of the atmospheric model was not sufficient to break the Maritime continent Barrier and thus to improve the skill of TIO forecast A better set of initial conditions is shown to be crucial for improving skill by 3-5 days. Both better representation of the state of the atmosphere and better compatibility of the initial conditions with the forecast model appears to be important Intraseasonal variations of oceanic initial states are not well represented by the ocean analysis (GODAS). However, as ocean � atmosphere coupling is quite important for the TIO. It follows that inconsistencies between the ocean and atmospheric initial state at this portion of the spectrum may damage the forecast There are additional sources of predictability to take advantage from for subseasonal forecasting e.g., subseasonal prediction over the Sahel (Vintzileos and Thiaw, 2006)

44. Conclusions We have shown that a set of atmospheric initial conditions which is more realistic and more compatible with the forecast model is crucial for TIO forecast. This underlines the importance of the new reanalysis project carried out at NCEP. We have shown here that horizontal resolution is not critical for forecast of the TIO. However there are areas (Sahel) were resolution higher than T126 is beneficial. The next version of the CFS will be at T126. Could downscaling from T126 provide results as good as the ones obtained with a CFS at T254 in these areas? The role of oceanic initial conditions has not yet been explored. How to improve the intraseasonal part of the ocean initial state?

45. Questions?