Skip to main content

Predictability of South American low-level jet using QuikSCAT ocean surface wind

Buy Article:

$60.90 plus tax (Refund Policy)


The applicability of NASA QuikSCAT ocean surface wind was tested for predicting South American low-level jets (SALLJs) with a statistical model. Our previous study (Wang, H. and Fu, R., 2004, Influence of cross-Andes flow on the South American low-level jet. Journal of Climate, 17, pp. 1247-1262) has examined the dynamic process associated with austral winter SALLJs using the ECMWF Reanalyses (ERA) and identified the mechanism that controls the seasonal and synoptic variations of the SALLJ. It was found that the SALLJ is maintained by strong zonal pressure gradients, with a maximum near 850 hPa caused by deflection of upstream zonal flow crossing the Andes and lee cyclogenesis. The robustness of this mechanism was further examined in this study using the NCEP-NCAR Reanalysis 1 (NCEP-R1) and NCEP-DOE Reanalysis 2 (NCEP-R2). The northerly LLJs to the east of the Andes are strongest in ERA, with wind speeds well above 15 m s-1. In NCEP-R1 and R2, typical wind speeds are about 12 and 10 m s-1, respectively. A statistical analysis of the three reanalysis datasets indicates that the SALLJ significantly correlates with the zonal wind of previous days over the South Pacific, particularly with the surface zonal wind. Based on this result, a statistical model introduced in Wang and Fu (2004) was employed in this study for forecasting the SALLJ using the QuikSCAT ocean surface wind as a predictor. The model was applied to June, July and August of 1999 to 2006 for up to 5 day forecasts of the SALLJ. Cross validations of the hindcasts indicate significant predictability of strong LLJ events with the QuikSCAT ocean surface wind data.

Document Type: Research Article


Affiliations: 1: School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA,Climate Prediction Center, NCEP/NWS/NOAA, Camp Springs, MD 20746, USA,Wyle Information Systems, McLean, VA 22102, USA 2: School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA 3: Climate Prediction Center, NCEP/NWS/NOAA, Camp Springs, MD 20746, USA 4: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA

Publication date: 2008-11-01

More about this publication?
  • Access Key
  • Free ContentFree content
  • Partial Free ContentPartial Free content
  • New ContentNew content
  • Open Access ContentOpen access content
  • Partial Open Access ContentPartial Open access content
  • Subscribed ContentSubscribed content
  • Partial Subscribed ContentPartial Subscribed content
  • Free Trial ContentFree trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more