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On the Dynamical Predictability of Summer Monsoon Depressions over South Asia

On the Dynamical Predictability of Summer Monsoon Depressions over South Asia. Yi-Chi Wang and Wen-wen Tung Earth and Atmospheric Sciences Purdue University West Lafayette, Indiana, USA (wang201@purdue.edu; wwtung@purdue.edu)

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On the Dynamical Predictability of Summer Monsoon Depressions over South Asia

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  1. On the Dynamical Predictability of Summer Monsoon Depressions over South Asia Yi-Chi Wang and Wen-wen Tung Earth and Atmospheric SciencesPurdue University West Lafayette, Indiana, USA (wang201@purdue.edu; wwtung@purdue.edu) Acknowledgements:Hsin-I Chang, J. B. Gao, Jui-Lin Li, Dev NiyogiPurdue Rosen Center for Advanced Computing, WRF-HelpNSF CMMI-0826119 --- The Impact of Cloud-System-Resolving Modeling

  2. Outline • South Asian Summer Monsoon Depressions • Case study (August 1-7, 2006) in observations • Hindcasts utilizing Advance Research WRF (ARW) • Control Hindcast with 10-km horizontal resolution • Ensemble Experiment • Cloud-System-Resolving Hindcast with 3.33-km resolution • Core Structure in Cloud-System-Resolving Hindcast • Summary and Discussions

  3. South Asian Summer Monsoon Depressions • Genesis • During Indian summer monsoon season; on average two depressions occur each month. Majority forms over the Bay of Bengal; Gross horizontal scale several thousand km • Propagation • Depressions occurring over the Bay of Bengal commonly move westward towards Indian Subcontinent. After landfall, they may turn to northward or keep westward and eventually merge to the Pakistan seasonal low. • Intensity • Accumulated rain can reach up to 20cm in 24hours. Most rainfall occurs at the southwest quadrant of the depression. • Observational and theoretical studies • Before Summer MONEX 1979: Sikka(1977), Krishnamurti et al. (1975), Godbole(1977) • After Summer MONEX 1979: Nitta and Masuda(1981), Saha and Chang(1983), Sanders(1984), Douglas (1992 ab)

  4. Case Study: A deep depression during August 02-05, 2006Meteorological Office, Pune, India. Mausam, 58 (2007) 08/01: well-marked low area 08/02 0300 UTC :Depression 08/02 0900 UTC: Deep Depression 08/03 0300 UTC: Deep Depression 08/04 0300 UTC: Deep Depression 08/04 1200 UTC: Depression 08/05 0300 UTC: Depression 08/05 PM: well-marked low It continued to move west- northwest-ward and eventually merged with the heat low in southeast Rajasthan during 08/12-14. Loss of life: 251 North coastal Andhra Pradesh: 62 Orissa: 45 Madhya Pradesh: 55 Vidarbha: 13 Marathwada: 76

  5. Motivation • Great societal and economic significance of the rainfall brought by Monsoon Depressions which call for accurate track and intensity forecasts. • What could possibly improve the forecasts of monsoon depressions? • Ensemble predictions • Raise model resolution to cloud-system-resolving resolution. Cloud-system-resolving modeling have been shown to be promising in hindcasting multiscale tropical convective systems (e.g. Miura et al. 2007, Science).

  6. Datasets • TRMM (Tropical Rainfall Measuring Mission) • 3B42, 3-hrly, 0.25ox0.25o gridded rain rate data • Multi-satellite merged TRMM real-time passive microwave (HQ) and geostationary IR-estimated precipitation. • NCEP/NCAR Reanalysis • 6-hrly, 17 pressure levels, 2.5ox2.5o gridded data • Including dynamic and thermodynamic fields • QuickScat • Level 3, daily, 0.25o x 0.25o, gridded • ocean wind vectors from satellite scatterometer. • Indian Meteorological Office observations • Observations on the depression center during Aug 2 to Aug 5 2006 • Precipitation of major cities are documented

  7. Mean Fields during Aug01 0000UTC to Aug08 0000UTC in Observations • Seven-day Mean fields averaged over Aug 1st to Aug 7th, 2006 – a typical mature monsoon situation 850-hPa Temperature and Wind Fields (NCEP/NCAR reanalysis) Rainfall Rate(TRMM) and 200-hPa Wind Fields (NCEP/NCAR reanalysis)

  8. Model Setups • ARW (Advanced Research WRF) • Two-way nested domains • Two-Domain Hindcast (Control Run): • D1 (30km) + D2 (10km) • Cumulus parameterizations turned on in both domains • D1 : July 25 00UTC – Aug 8 00UTC • D2 : July 31 00UTC – Aug 8 00UTC • Three-Domain Hindcast: CSRM (Cloud-system-Resolving Modeling): • D1(30km) + D2 (10km) + D3 (3.33km) • D1 and D2 as the two-domain run • D3 : July 31 00UTC – Aug 8 00UTC • Cumulus parameterization turned off leaving explicit scheme • Lateral and Initial Boundary Conditions • FNL analysis • NCEP RTG Sea Surface Temp • Parameterizations : • - Grell-Devenyi ensemble cumulus parameterization • - WRF Single-Moment 6-class microphysics (WSM6) • - Yonsei University PBL • - Noah Land Surface model

  9. Ensemble Experiment Ensemble tracks and sea level pressure minimum from August 01 to 05, 2006 • 20 ensemble members in the two-domain setup • Ensembles are generated by adding Gaussian perturbations to the in u, v, and T in the control run at 0000UTC on Aug 01, 2006.

  10. Animation Link

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  12. Animation Link

  13. 7-day Mean Ensemble (blue) and CSRM (pink) Rain Rates Aug 1--7, 2006 Green contours: TRMM 3B42(mm/hr)

  14. Wind fields Core Structure revealed by CSRM 200hPa 0900 UTC Aug 01 • Core structure is closely related to the propagation and excitation mechanisms. 850hPa 300hPa Vertical wind

  15. temperature and (u, w) anomalies 0900UTC Aug 1 2006 Cross-section A Cross-section B W W W W C C SLP Rainfall

  16. Summary and Conclusions • The 10-km D02 ARW hindcast captures the genesis & overall propagation of the depression during Aug. 01-07, 2006. However, • The south bend of the track is missing. • The precipitation is underestimated and misplaced over the northern India rather than the central India after 36-60 hours. • The preliminary ensemble experiment does not fix the track and intensity problems. The hindcast may not be very sensitive to the perturbations of the initial conditions. • The hindcast is however sensitive to the choices of physics such as cumulus and PBL parameterizations, as well as, in one study, soil moisture feedback (e.g., Chang et al., 2008)

  17. Summary and Conclusions • Comparing with the control run, the cloud-system-resolving run has better performance: • Southward bend is captured. • Better track with better rainfall distribution till 72 hours. • This suggests that the model’s ability to resolve the multiscale interactions involving convective systems is crucial for obtaining correct energetics, scale selections, etc. associated with the depression

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