Pan American Climate Studies (PACS)

AOML/PHOD Project Titles:

Inter-American Climate and Atlantic Ocean Variability (Enfield)
Mixed Layer Heat Transport in the Eastern Equatorial Pacific (Swenson)

NOAA Strategic Plan Element:

"Implement Seasonal-to-Interannual Climate Forecasts"

Principal Investigators and Area of Concentration:

Dr. David B. Enfield: XBTs, other observations and model fields
Dr. Mark S. Swenson: Drifters, other observations and model fields

The programmatic scope of PACS:

PACS is a joint program of the NOAA Office of Global Programs (OGP) and the Office of Oceanic and Atmospheric Research (OAR)/ Environmental Research Laboratories (ERL). PACS falls wi thin the scope of the U.S. GOALS (Global Ocean-Atmosphere-Land System) Program and addresses the advancement of our ability to predict seasonal to interannual climate variability over the Americas with an emphasis on precipitation.

The AOML PACS activities:

Drs. Enfield and Swenson are in the second of two PACS-funded biennial project cycles. The first (1994-1996), a single project entitled "Empirical Ocean Climate Studies" involved both PIs working together with coworkers and graduate students on the thematic areas listed below. In the second cycle (1996-1998) the PIs split into separate projects entitled "Inter-American Climate and Atlantic Ocean Variability" (Enfield, first and third objectives) and "Mixed Layer Heat Transport in the Eastern Equatorial Pacific" (Swenson, second and third objectives).

The AOML/PHOD project objectives (connecting to progress and plans):

Determine the scales and domains of tropical Atlantic and Pacific SST variability to which inter-American climate fluctuations are most sensitive.
Use large scale data sets to assess -- through direct comparison of corresponding data and model fields -- the retrospective and diagnostic performance of the NMC operational OGCM as well as the associated coupled-model forecasts.
Retrospectively examine the upper ocean heat balance based on the best data fields currently available and use this as a means to further diagnose how well model-derived fields reproduce the processes that effect changes in the SST distributions.