scholarly journals Decadal Variations of North Atlantic Sea Surface Temperature in Observations and CMIP3 Simulations*

2010 ◽  
Vol 23 (17) ◽  
pp. 4619-4636 ◽  
Author(s):  
Nathan Jamison ◽  
Sergey Kravtsov
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
North Atlantic ◽  
Climate Models ◽  
Decadal Variability ◽  
Singular Spectrum Analysis ◽  
Global Climate Models ◽  
Sea Surface ◽  
Decadal Variations

Abstract This study evaluates the ability of the global climate models that compose phase 3 of the Coupled Model Intercomparison Project (CMIP3) to simulate intrinsic decadal variations detected in the observed North Atlantic sea surface temperature (SST) record via multichannel singular spectrum analysis (M-SSA). M-SSA identifies statistically significant signals in the observed SSTs, with time scales of 5–10, 10–15, and 15–30 yr; all of these signals have distinctive spatiotemporal characteristics and are consistent with previous studies. Many of the CMIP3 twentieth-century simulations are characterized by quasi-oscillatory behavior within one or more of the three observationally motivated frequency bands specified above; however, only a fraction of these models also capture the spatial patterns of the observed signals. The models best reproduce the observed quasi-regular SST variations in the high-frequency, 5–10-yr band, while the observed signals in the intermediate, 10–15-yr band have turned out to be most difficult to capture. A handful of models capture the patterns and, sometimes, the spectral character of the observed variability in the two or three bands simultaneously. These results imply that the decadal prediction skill of the models considered—to be estimated within the CMIP5 framework—would be stratified according to the models’ performance in capturing the time scales and patterns of the observed decadal SST variations. They also warrant further research into the dynamical causes of the observed and simulated decadal variability, as well as into apparent differences in the representation of these variations by individual CMIP3 models.

scholarly journals CMIP6 model-based analog forecasting for the seasonal prediction of sea surface temperature in the offshore area of China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Weiying Peng ◽  
Quanliang Chen ◽  
Shijie Zhou ◽  
Ping Huang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Models ◽  
Global Climate Models ◽  
Sea Surface ◽  
Seasonal Forecasts ◽  
Initial State ◽  
Initial Field ◽  
Offshore Area ◽  
Model Based

AbstractSeasonal forecasts at lead times of 1–12 months for sea surface temperature (SST) anomalies (SSTAs) in the offshore area of China are a considerable challenge for climate prediction in China. Previous research suggests that a model-based analog forecasting (MAF) method based on the simulations of coupled global climate models provide skillful climate forecasts of tropical Indo-Pacific SSTAs. This MAF method selects the model-simulated cases close to the observed initial state as a model-analog ensemble, and then uses the subsequent evolution of the SSTA to generate the forecasts. In this study, the MAF method is applied to the offshore area of China (0°–45°N, 105°–135°E) based on the simulations of 23 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the period 1981–2010. By optimizing the key factors in the MAF method, we suggest that the optimal initial field for the analog criteria should be concentrated in the western North Pacific. The multi-model ensemble of the optimized MAF prediction using these 23 CMIP6 models shows anomaly correlation coefficients exceeding 0.6 at the 3-month lead time, which is much improved relative to previous SST-initialized hindcasts and appears practical for operational forecasting.

scholarly journals On the Interpretation of the North Atlantic Averaged Sea Surface Temperature

2020 ◽  
Vol 33 (14) ◽  
pp. 6025-6045
Author(s):  
Jing Sun ◽  
Mojib Latif ◽  
Wonsun Park ◽  
Taewook Park
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Climate Models ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
The North ◽  
Sst Variability ◽  
The North Atlantic ◽  
Different Time Scales

AbstractThe North Atlantic (NA) basin-averaged sea surface temperature (NASST) is often used as an index to study climate variability in the NA sector. However, there is still some debate on what drives it. Based on observations and climate models, an analysis of the different influences on the NASST index and its low-pass filtered version, the Atlantic multidecadal oscillation (AMO) index, is provided. In particular, the relationships of the two indices with some of its mechanistic drivers including the Atlantic meridional overturning circulation (AMOC) are investigated. In observations, the NASST index accounts for significant SST variability over the tropical and subpolar NA. The NASST index is shown to lump together SST variability originating from different mechanisms operating on different time scales. The AMO index emphasizes the subpolar SST variability. In the climate models, the SST-anomaly pattern associated with the NASST index is similar. The AMO index, however, only represents pronounced SST variability over the extratropical NA, and this variability is significantly linked to the AMOC. There is a sensitivity of this linkage to the cold NA SST bias observed in many climate models. Models suffering from a large cold bias exhibit a relatively weak linkage between the AMOC and AMO and vice versa. Finally, the basin-averaged SST in its unfiltered form, which has been used to question a strong influence of ocean dynamics on NA SST variability, mixes together multiple types of variability occurring on different time scales and therefore underemphasizes the role of ocean dynamics in the multidecadal variability of NA SSTs.

scholarly journals Predictability and Decadal Variability of the North Atlantic Ocean State Evaluated from a Realistic Ocean Model

2017 ◽  
Vol 30 (2) ◽  
pp. 477-498 ◽  
Author(s):  
Florian Sévellec ◽  
Alexey V. Fedorov
Keyword(s):  
Atlantic Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Decadal Variability ◽  
North Atlantic Ocean ◽  
Meridional Overturning Circulation ◽  
Sea Surface ◽  
The North ◽  
The North Atlantic

This study investigates the excitation of decadal variability and predictability of the ocean climate state in the North Atlantic. Specifically, initial linear optimal perturbations (LOPs) in temperature and salinity that vary with depth, longitude, and latitude are computed, and the maximum impact on the ocean of these perturbations is evaluated in a realistic ocean general circulation model. The computations of the LOPs involve a maximization procedure based on Lagrange multipliers in a nonautonomous context. To assess the impact of these perturbations four different measures of the North Atlantic Ocean state are used: meridional volume and heat transports (MVT and MHT) and spatially averaged sea surface temperature (SST) and ocean heat content (OHC). It is shown that these metrics are dramatically different with regard to predictability. Whereas OHC and SST can be efficiently modified only by basin-scale anomalies, MVT and MHT are also strongly affected by smaller-scale perturbations. This suggests that instantaneous or even annual-mean values of MVT and MHT are less predictable than SST and OHC. Only when averaged over several decades do the former two metrics have predictability comparable to the latter two, which highlights the need for long-term observations of the Atlantic meridional overturning circulation in order to accumulate climatically relevant data. This study also suggests that initial errors in ocean temperature of a few millikelvins, encompassing both the upper and deep ocean, can lead to ~0.1-K errors in the predictions of North Atlantic sea surface temperature on interannual time scales. This transient error growth peaks for SST and OHC after about 6 and 10 years, respectively, implying a potential predictability barrier.

Multi- and Quasi-Decadal Variations of Sea Surface Temperature in the North Atlantic

1999 ◽  
Vol 29 (12) ◽  
pp. 3133-3144 ◽  
Author(s):  
Ken-ichi Mizoguchi ◽  
Steven D. Meyers ◽  
Sujit Basu ◽  
James J. O’Brien
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Sea Surface ◽  
The North ◽  
Decadal Variations ◽  
The North Atlantic

scholarly journals North Atlantic climate variability in coupled models and data

2008 ◽  
Vol 15 (1) ◽  
pp. 13-24 ◽  
Author(s):  
S. K. Kravtsov ◽  
W. K. Dewar ◽  
M. Ghil ◽  
P. S. Berloff ◽  
J. C. McWilliams
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Large Scale ◽  
Climate Models ◽  
Three Dimensional ◽  
Sea Surface ◽  
Coupled Models ◽  
Ocean Atmosphere

Abstract. We show that the observed zonally averaged jet in the Northern Hemisphere atmosphere exhibits two spatial patterns with broadband variability in the decadal and inter-decadal range; these patterns are consistent with an important role of local, mid-latitude ocean–atmosphere coupling. A key aspect of this behaviour is the fundamentally nonlinear bi-stability of the atmospheric jet's latitudinal position, which enables relatively small sea-surface temperature anomalies associated with ocean processes to affect the large-scale atmospheric winds. The wind anomalies induce, in turn, complex three-dimensional anomalies in the ocean's main thermocline; in particular, they may be responsible for recently reported cooling of the upper ocean. Both observed modes of variability, decadal and inter-decadal, have been found in our intermediate climate models. One mode resembles North Atlantic tri-polar sea-surface temperature (SST) patterns described elsewhere. The other mode, with mono-polar SST pattern, is novel; its key aspects include interaction of oceanic turbulence with the large-scale oceanic flow. To the extent these anomalies exist, the interpretation of observed climate variability in terms of natural and human-induced changes will be affected. Coupled mid-latitude ocean-atmosphere modes do, however, suggest some degree of predictability is possible.

scholarly journals Insights into Decadal North Atlantic Sea Surface Temperature and Ocean Heat Content Variability from an Eddy-Permitting Coupled Climate Model

2019 ◽  
Vol 32 (18) ◽  
pp. 6137-6161 ◽  
Author(s):  
B. I. Moat ◽  
B. Sinha ◽  
S. A. Josey ◽  
J. Robson ◽  
P. Ortega ◽  
...  
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Mixed Layer ◽  
North Atlantic ◽  
Climate Model ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Sea Surface

Abstract An ocean mixed layer heat budget methodology is used to investigate the physical processes determining subpolar North Atlantic (SPNA) sea surface temperature (SST) and ocean heat content (OHC) variability on decadal to multidecadal time scales using the state-of-the-art climate model HadGEM3-GC2. New elements include development of an equation for evolution of anomalous SST for interannual and longer time scales in a form analogous to that for OHC, parameterization of the diffusive heat flux at the base of the mixed layer, and analysis of a composite Atlantic meridional overturning circulation (AMOC) event. Contributions to OHC and SST variability from two sources are evaluated: 1) net ocean–atmosphere heat flux and 2) all other processes, including advection, diffusion, and entrainment for SST. Anomalies in OHC tendency propagate anticlockwise around the SPNA on multidecadal time scales with a clear relationship to the phase of the AMOC. AMOC anomalies lead SST tendencies, which in turn lead OHC tendencies in both the eastern and western SPNA. OHC and SST variations in the SPNA on decadal time scales are dominated by AMOC variability because it controls variability of advection, which is shown to be the dominant term in the OHC budget. Lags between OHC and SST are traced to differences between the advection term for OHC and the advection–entrainment term for SST. The new results have implications for interpretation of variations in Atlantic heat uptake in the CMIP6 climate model assessment.

Joint projections of North Pacific sea surface temperature from different global climate models

2012 ◽  
Vol 23 (5) ◽  
pp. 451-465 ◽  
Author(s):  
Francisco Beltrán ◽  
Bruno Sansó ◽  
Ricardo T. Lemos ◽  
Roy Mendelssohn
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Pacific ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Sea Surface

scholarly journals On the Correspondence between Seasonal Forecast Biases and Long-Term Climate Biases in Sea Surface Temperature

2020 ◽  
Vol 34 (1) ◽  
pp. 427-446
Author(s):  
Hsi-Yen Ma ◽  
A. Cheska Siongco ◽  
Stephen A. Klein ◽  
Shaocheng Xie ◽  
Alicia R. Karspeck ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Initial Conditions ◽  
Global Climate Models ◽  
Sea Surface ◽  
Substantial Part ◽  
Seasonal Forecasts ◽  
Climate Simulations

AbstractThe correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multimodel Ensemble, and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and subtropics than over the extratropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with time scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean–atmosphere models.

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