In a recent paper, we argued that ocean dynamics increase the variability of midlatitude sea surface temperatures (SSTs) on monthly to interannual time scales, but act to damp lower-frequency SST variability over broad midlatitude regions. Here, we use two configurations of a simple stochastic climate model to provide new insights into this important aspect of climate variability. The simplest configuration includes the forcing and damping of SST variability by observed surface heat fluxes only, and the more complex configuration includes forcing and damping by ocean processes, which are estimated indirectly from monthly observations. It is found that the simple model driven only by the observed surface heat fluxes generally produces midlatitude SST power spectra that are too
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In this paper we summarize improvements in climate model simulation of eastern boundary upwelling systems (EBUS) when changing the forcing dataset from the Coordinated Ocean-Ice Reference Experiments (CORE; ∼2° winds) to the higher-resolution Japanese 55-year Atmospheric Reanalysis for driving ocean–sea ice models (JRA55-do, ∼0.5°) and also due to refining ocean grid spacing from 1° to 0.1°. The focus is on sea surface temperature (SST), a key variable for climate studies, and which is typically too warm in climate model representation of EBUS. The change in forcing leads to a better-defined atmospheric low-level coastal jet, leading to more equatorward ocean flow and coastal upwelling, both in turn acting to reduce SST over the upwelling regions off the west coast of North America, Peru, and Chile. The refinement of ocean resolution then leads to narrower and stronger alongshore ocean flow and coastal upwelling, and the emergence of strong across-shore temperature gradients not seen with the coarse ocean model. Off northwest Africa the SST bias mainly improves with ocean resolution but not with forcing, while in the Benguela, JRA55-do with high-resolution ocean leads to lower SST but a substantial bias relative to observations remains. Reasons for the Benguela bias are discussed in the context of companion regional ocean model simulations. Finally, we address to what extent improvements in mean state lead to changes to the monthly to interannual variability. It is found that large-scale SST variability in EBUS on monthly and longer time scales is largely governed by teleconnections from climate modes and less sensitive to model resolution and forcing than the mean state.
more » « less- Award ID(s):
- 2231237
- PAR ID:
- 10566091
- Publisher / Repository:
- American Meteorological Society (AMS)
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 37
- Issue:
- 9
- ISSN:
- 0894-8755
- Page Range / eLocation ID:
- 2821 to 2848
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract red compared to observations. Including ocean processes in the model reduces this discrepancy bywhitening the midlatitude SST spectra. In particular, ocean processes generally increase the SST variance on <2-yr time scales and decrease it on >2-yr time scales. This happens because oceanic forcing increases the midlatitude SST variance across many time scales, but oceanic damping outweighs oceanic forcing on >2-yr time scales, particularly away from the western boundary currents. The whitening of midlatitude SST variability by ocean processes also operates in NCAR’s Community Earth System Model (CESM). That is, midlatitude SST spectra are generally redder when the same atmospheric model is coupled to a slab rather than dynamically active ocean model. Overall, the results suggest that forcing and damping by ocean processes play essential roles in driving midlatitude SST variability. -
Abstract This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air‐sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy‐resolving high‐resolution (HR) and eddy‐parameterized low‐resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co‐variability over scales between 50 and 10,000 km and 60 days to 80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper‐ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ∼2,000–2,500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (
R 1, ∼600–2,000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean forcing also induces oscillations in SST and THF with periods ranging from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that driven by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR. -
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