Quantifying SST Errors from an OGCM in Relation to Atmospheric Forcing Variables

Abstract

The relationship between various atmospheric variables at the sea surface and climatological monthly means of sea surface temperature (SST) is investigated over the global ocean. The goal is to quantify the change in SST that results solely from variations in a particular atmospheric variable. This is accomplished using a series of numerical simulations from an atmospherically-forced ocean general circulation model (OGCM). It is first demonstrated that SST variations at all latitudes are generally strongly and positively correlated with increases in near-surface air temperature, and vapor mixing ratio and net shortwave radiation at the sea surface, while they are often moderately and negatively correlated with increases in near-surface wind speed. There is only a weak and negative relationship between variations in SST and those in net longwave radiation at the sea surface. Variations in the net shortwave radiation and vapor mixing ratio are found to have more influence in driving the seasonal cycle of SST than other atmospheric variables. Results from the factorial design are somewhat consistent with the simple linear regression analysis, in that a 2 degree C increase in air temperature can typically give an increase in SST, generally ranging between 0.5 degree C and 0.8 degree C over the global ocean.

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Document Details

Document Type
Technical Report
Publication Date
Mar 03, 2009
Accession Number
ADA503017

Entities

People

  • A. Birol Kara
  • Alan J. Wallcraft
  • Harley E. Hurlburt
  • Wei-yin Loh

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Air Temperature
  • Data Science
  • Factorial Design
  • Grids
  • Heat Energy
  • Information Science
  • Latitude
  • Linear Regression Analysis
  • Military Research
  • Oceanography
  • Radiation
  • Regression Analysis
  • Sea Surface Temperature
  • Simulations
  • Statistical Analysis
  • Statistics
  • Surface Temperature

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Regression Analysis.