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Tereza Cavazos NAME Working Group Puerto Vallarta, Mexico November 2003 CICESE and UABC Participation in NAME Intro Dept. of Physical Oceanography 2002.

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Presentation on theme: "Tereza Cavazos NAME Working Group Puerto Vallarta, Mexico November 2003 CICESE and UABC Participation in NAME Intro Dept. of Physical Oceanography 2002."— Presentation transcript:

1 Tereza Cavazos NAME Working Group Puerto Vallarta, Mexico November 2003 CICESE and UABC Participation in NAME Intro Dept. of Physical Oceanography 2002 Components: - Oceanographic - Atmospheric - Land-Surface Title

2 Oceanographic Comp MW Douglas - NSSL AS Mascarenhas - UABC MF Lavin – CICESE, Ens. R Castro - UABC E Beier – CICESE, La Paz D Mitchell - DRI P Guest - NPS D Ivanova - DRI The Role of Oceanic Processes on the Gulf of California SST Evolution During the NAME Oceanographic Component

3 SST_clim: Sat JPL AVHRR Pathfinder Global 9 Km SST Climatology HYPOTHESIS: Northward advance of the monsoon seems to be related to the poleward progression of the 26 o C isotherm on the eastern side of the GC http://podaac.jpl.nasa.gov/climatology

4 Corr_SST: Model June to September monthly climatology of currents (cms -1 ) and temperature ( o C) in the 25-50 m layer of the POCM-4C model. September JuneJuly August Observations: TSW at the entrance of the GC  Max in May-Jun - Castro et al. 2000 - Castro 2001 - Mascarenhas et al. 2003

5 Corr:Model Modeling the circulation and heat fluxes in the GC (G. Marinone & A. Parés)

6 QuickScat Surface Wind Climatology Using QuikScat (G. Marinone & A. Parés)

7 Scientific Question What is the relative importance of oceanic heat advection and local-air sea fluxes in controlling the SST evolution during the NAM in the Gulf of California ? Objective The Role of Oceanic Processes on the Gulf of California SST Evolution During the NAME Oceanographic Component

8 Cruises - Observing stations along the blue lines - CTD every 10 km and down to 1000m - Atmospheric soundings 4/day - Continuous meteorological, ADCP and SST data will be collected throughout the cruises -The coastal meteorological stations and ADCP+MicroCAT moorings will be deployed at both sides of the GC - Large dots: possible deployment sites for surface satellite-tracked drifters Proposed NAME Oceanographic Cruises

9 Objective 1: Determine characteristics of convective phenomena - GOES satellite imagery - Surface and upper-air observations - Mesoscale model simulations (MM5) AtmosComp Convective Patterns Over Baja California (LM Farfán – CICESE, La Paz) Atmospheric Component

10 LF2 - Large-scale conditions and dynamic mechanisms - Changes in structure due to storm interaction with the peninsula - Determine patterns of wind/rainfall distribution to identify high-risk areas Hurricane Marty: 12UTC 22 September 2003 Objective 2: Study landfall tracks in Baja California

11 Land-Sfc D. Lettenmaier, T. Cavazos & C. Zhu Land-surface hydrologic predictability in the NAM region using a derived long-term data set 1 To what extent do soil moisture and snow anomalies affect the evolution of the NAM? Science Question

12 Extend retrospective LDAS data set to cover Tiers 1, 2 and 3 for ~ 50 yrs Objectives Using the derived LDAS, undertake predictability studies to investigate the role of land-surface feedbacks in the monsoon region Current soil moisture data (LDAS; 1950-97): Derived from a variable infiltration capacity (VIC) model with 1/8º resolution (Maurer et al. 2002). Study Domain Tier 3

13 Winter Precipitation-monsoon rainfall feedback hypothesis Higher (lower) winter precipitation & spring snowpack More (less) spring & early summer soil moisture Lower (higher) spring & early summer surface temperature Hypothesis Weak (strong) monsoon

14 Study area Monsoon West Monsoon South Monsoon North Monsoon East Precipitation Regions

15 Winter Precip JFM Precipitation in extreme monsoon years DRYWET Wet MonsoonDry Monsoon Apr-May Soil Moisture in extreme monsoon years Snow DRY WET

16 Moisture WetDry Soil moisture anomalies persist from spring until June What is the feedback to the atmosphere ?

17 SWE_Ts Correlation May-Jun SWE and Surface temperature (Ts) (Negative relationship) Correlation June Ts vs July Precipitation

18 Wet modes Heterogeneous SVD JAS Z500 vs JAS Precipitation Dry ?

19 SST Heterogeneous SVD JFM SST vs JAS Precipitation -0.4 0.4 -0.4 Negative PDO  Dry monsoon

20 SVD: Z500 (AMJ) & PPT (JAS) Mode 1: Z500 (AMJ) JAS Pan: NWMex & AZ DRY WET Z500

21 Conclusions Higher (lower) winter precipitation & spring snowpack More (less) spring & early summer soil moisture Lower (higher) spring & early summer surface temperature Weak (strong) monsoon Atmospheric connection : Winter SSTan and Spring Z500 circulation Especially During Extreme Years Conclusions

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