Relationship between SST gradients and upwelling off Peru and Chile: model/satellite data analysis

ABSTRACT

The upwelling system off Peru/Chile is characterized by significant mesoscale to submesoscale surface variability that results from the instability of the coastal currents (due to the strong vertical and horizontal shears) and to the marked density cross-shore gradients (associated with the mean upwelling). Here we investigate to what extent upwelling intensity can be inferred from sea surface temperature (SST) derived from remote sensing. As a first step in validation, a comparison between SST observations is performed, which indicates that the 1 km gridded multi-scale ultra-high-resolution (MUR) SST data set is defining a zone of maximum SST gradients closer to shore than the low-resolution National Centers for Environmental Information 0.25° resolution data set. Two model versions, at nominal resolutions of 2 km and 4 km, of the Massachusetts Institute of Technology general circulation model are analysed. A high-resolution version at 2 km is examined for the period 13 September 2011–23 January 2013, while a 4 km version is examined for 6 March 2011–22 April 2013. MUR shows maxima SST gradients in the range of 0.03 ± 0.02 K km⁻¹ while the model showed higher gradients around 0.05 ± 0.02 K km⁻¹. Based on coherence spectra, the relationship between upwelling rate (as inferred from the vertical velocity) and SST gradient is documented in the model from intraseasonal to annual timescales. It suggests that changes in SST gradient magnitudes are related to changes in the intensity of coastal upwelling off Peru and Chile. Such a relationship between SST gradients and vertical velocity would allow for the use of satellite-derived SSTs to monitor the intensity of coastal upwelling from the intraseasonal to annual timescales.

Acknowledgments

The work was carried out under contract with the National Aeronautics and Space Administration (NASA) at the Jet Propulsion Laboratory/California Institute of Technology. Specifically the work was funded through the Multi-Sensor Improved Sea Surface Temperature Project (MISST). The authors specifically acknowledge that SST data sets were acquired through the Group for High Resolution Sea Surface Temperature (GHRSST). The LLC4320 model is funded through NASA. We would also like to thank anonymous reviewers for their thoughtful comments. Also, we thank Professor Jose Gomez Valdes who proofread the article while on sabbatical at the Jet Propulsion Laboratory. More information on the MUR data set may be found at: http://mur.jpl.nasa.gov/. Data descriptions may also be found at: http://podaac-www.jpl.nasa.gov/dataset/JPL-L4UHfnd-GLOB-MUR. More information may be found here: JPL MUR MEaSUREs Project. 2010. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 2. PO. DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at http://dx.doi.org/10.5067/GHGMR-4FJ01.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Multi-Sensor Improved Sea Surface Temperature Project (MISST), NASA.