Variations of the Asian Monsoon and Simulations and Predictions by the NCEP CFS Song Yang

Transcription

1 Variations of the Asian Monsoon and Simulations and Predictions by the NCEP CFS Song Yang NOAA Climate Prediction Center, Camp Springs, Maryland, USA

2 Contents, Coauthors, and References 1. Variability and prediction (including role of ENSO) Liang, J., S. Yang, Z.-Z. Hu, B. Huang, A. Kumar, and Z. Zhang, 2009: Predictable patterns of Asian and Indo- Pacific summer precipitation in the NCEP CFS. Climate Dynamics, 32, Yang, S., M. Wen, and R. W. Higgins, 2008: Sub-seasonal features of the Asian summer monsoon in the NCEP Climate Forecast System. ACTA Oceanologica Sinica, 27, *Yang, S., Z. Zhang, V. E. Kousky, R. W. Higgins, S.-H. Yoo, J. Liang, and Y. Fan, 2008: Simulations and seasonal prediction of the Asian summer monsoon in the NCEP Climate Forecast System. J. Climate, 21, Impact of land surface models Yang, S., M. Wen, R. Yang, K. Mitchell, and J. Meng, 2009: Impact of land surface processes on the simulation and prediction of Asian summer monsoon by the NCEP CFS. In preparation. 3. Impacts of model resolutions and initial conditions Wen, M., S. Yang, A. Vintzileos, and R. W. Higgins, 2009: Impacts of model resolutions and initial conditions on the simulation and prediction of Asian monsoon by the NCEP CFS. In preparation.

3 Contents, Coauthors, and References (cont.) 4. East Asian Mei-yu/Baiu/Changma Gao, H., S. Yang, A. Kumar, Z.-Z. Hu, B. Huang, Y. Li, and B. Jha, 2009: Variability of the East Asian Mei-yu climate and simulation-prediction by the NCEP CFS. J. Climate, to be submitted. 5. East Asian winter monsoon Li, Y., S. Yang, R. Wu, R. W. Higgins, and H. Gao, 2009: Variability of the East Asian winter monsoon and simulation-prediction by the NCEP CFS. In preparation.

4 The NCEP Climate Forecast System (CFS) and output An operational climate forecast system since August 2004 Two fully-coupled nine-month forecasts made every day Atmosphere: NCEP Global Forecast System, but in T62 Ocean: MOM-3 Land: Oregon State University 2-layer model (OSU) A new CFS implementation expected in 2010: T126, MOM-4, Noah 4-L land model Hindcasts: (1) T62: 15 ensemble members, /06, & 9-month integration; (2) T126: 10 members, , & 6-month integration; (3) T62, T126, & T254: 4 members, , & 60-day integration (one T382 experiment) Free runs: T62 (50 years) and T126 (100 years)

5 1. Simulation and Prediction JJA mean precipitation

6 Sub-seasonal time scales (MJO, QBWO, and SYNO): OLR variances

7 Interannual variability: Monsoon indices Webster-Yang monsoon index (Webster and Yang 1992) South Asian monsoon index (Goswami et al. 1999) SE Asian monsoon index (Wang and Fan 1999) East Asian monsoon index (Lau et al. 2000)

8 Skills of prediction Webster-Yang index (WY 1992), South Asia (Goswami et al. 1999), Southeast Asia (Wang and Fan 1999), East Asia (Lau et al. 2000) High skill even with Dec-Jan ICs

9 Role of ENSO in prediction (Composite for ENSO development phase)

10 Role of ENSO in prediction (Composite for ENSO decay Phase)

11 Maximum signal-to-noise EOF analysis (first mode) 1. Most predictable pattern 2. Authenticity 3. Lead time 4. Relation to ENSO

12 Maximum signal-to-noise EOF analysis (second mode)

13 2. Impact of Land Surface Models Cold bias

14 Weak large-scale monsoon circulation

15 Impact of LSM on temperature Land surface models: from OSU to Noah

16 Impact of LSM & LSP on temperature (cont.) (Land surface model and land surface process)

17 Impact of LSM on monsoon circulation Land surface models: from OSU to Noah Experimental Runs Apr-May ICs

18 Impact of LSM & LSP on precipitation (Land surface model and land surface process) OSU => Noah GR2 => GLDAS

19 3. Impacts of Model Resolutions & ICs T62 and T126 JJA SON T62 T126

20 From T62 and T126 to T382 Yoo et al. (2009)

21 Sub-seasonal time scales Obs X T126 T62 X T254

22 Sub-seasonal time scales (cont.) India ICP SCS

23 Impact of initial conditions (skipped)

24 4. Summary 1. Simulation and prediction by current model Good skills for various timescales, ENSO impact, most predictable modes, Cold bias, weak mean monsoon 2. Impact of land surface models Improvements from simple 2-L OSU to 4-L Noah, and from R-2 to GLDAS 3. Impact of resolutions Improvement from T62 to T126 for TP and IOD (T382 better) Sub-seasonal: improvement over India but not SCS 4. Impact of initial conditions (skipped)