Large-scale Sea Surface Temperature Anomalies Research Articles

ENSO and PDO Effect on Stratospheric Dynamics in Isca Numerical Experiments

The deterministic forecast of the stratospheric polar vortex intensity (iSPV) is limited by 2 weeks, but it can be probabilistically predicted for a longer period due to low-frequency components of the climate system, such as large-scale sea surface temperature anomalies (SSTAs) (e.g., El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)). For a qualitative and quantitative assessment of the effect of the large-scale Pacific SSTAs on the iSPV anomalies formation, idealized model experiments were carried out using the Isca platform. There is no statistically significant response of the SPV dynamics to the SSTAs corresponding to PDO phases, but they noticeably correct the effect of ENSO modes when added to it. The effect of the El Niño (EN) and La Niña (LN) events with neutral PDO phases on the iSPV is asymmetric; in the “single” EN experiment the vortex is 40% weaker relative to the control values, and, in the “single” LN, the SPV is weakened by no more than 20%. When EN accompanied with the positive PDO phase, iSPV is reduced by 58%. When the negative PDO phase is added, the EN effect is significantly weakened. The LN effect is weakened by both positive and negative PDO phases.

Synchronous Variation Patterns of Monthly Sea Ice Anomalies at the Arctic and Antarctic

Abstract Sea ice variability in the opposite polar regions is examined holistically by applying the self-organizing map (SOM) method to global monthly sea ice concentration data over two periods. The results show that the variability modes of sea ice decrease in the Arctic correspond to an overall sea ice increase in the Antarctic, and vice versa. In particular, the monthly sea ice anomaly patterns are dominated by in-phase variability across the Arctic that is stronger in the marginal seas particularly the Barents Sea than the central Arctic Ocean. The corresponding Antarctic sea ice variability is characterized by a zonal wavenumber-3 structure or a dipole pattern of out-of-phase variability between the Bellingshausen/Amundsen Seas and the rest of the Southern Ocean. The frequency of occurrence of these dominant patterns exhibits pronounced seasonal as well as decadal variability and the latter is closely related to the Pacific decadal oscillation and Atlantic multidecadal oscillation. Other less frequent patterns seem to be associated with the central Pacific El Niño and spatially heterogeneous interannual variability of sea surface temperature (SST) in the Indian and the Atlantic Oceans. The dominant modes explain 57% of the four-decade domain-averaged trends in the annual polar sea ice concentration, with more explained in the eastern than western Arctic Ocean and in the Weddell Sea and the Amundsen Sea in the Antarctic. The spatial patterns of the leading modes can be largely explained by the dynamic (sea ice drift) and thermodynamic (sea ice melt) effects of the anomalous atmospheric circulations associated with SST and sea level pressure anomalies. Significance Statement The purpose of this study is to extract the main modes of monthly global sea ice concentration variability in the past four decades, explain the mechanisms behind the occurrences of these modes, and examine the contributions of these modes to the trend in annual global sea ice concentration. Sea ice extent in the past four decades has shown a significant declining trend in the Arctic and a slight, but significant increasing trend in the Antarctic. By jointly analyzing the sea ice variability and trends in the two polar regions, the results here provide a reference for what might have contributed to the opposite sea ice trends in Arctic and Antarctic and highlight the important influence of large-scale sea surface temperature anomalies on the trends in the two polar regions.

Warm-season temperatures since 1600 BC reconstructed from Tasmanian tree rings and their relationship to large-scale sea surface temperature anomalies

We describe an improved tree-ring reconstruction of mean warm-season (November–April) temperatures for Tasmania from Huon pine. This record extends back to 1600 BC and is based on a tree-ring chronology that was processed to retain as much low-frequency variance as possible. The resulting reconstruction explains 46.6% of the variance and verifies significantly when compared to withheld instrumental data. Cross-spectral analysis of actual and estimated temperatures over the 1886–1991 common period indicates that most of the unexplained variance is at periods 12 years, the squared coherency ranges between 0.6–0.8, and the cross-spectral gain indicates that the amplitude of the reconstruction is a nearly unbiased estimate of the true temperature amplitude. Therefore, this reconstruction should be especially useful for studying multi-decadal temperature variability in the Tasmanian sector of the Southern Hemisphere over the past 3592 years. To this end, we examined the time evolution of low-frequency temperature amplitude fluctuations and found evidence for a 35% amplitude reduction after AD 100 that persisted until about AD 1900. Since that time, the low-frequency temperature amplitude has systematically increased. We also show how this reconstruction is related to large-scale sea surface temperatures (SST) in the Indian Ocean and eastward to the dateline. Pointwise correlations between the Tasmanian record and SSTs reveal a relationship that extends across the southern Indian Ocean and towards the Arabian Sea. This pattern is largely determined by inter-decadal temperature variability, with correlations in this > 10-year bandwidth commonly exceeding 0.6 over most of the southern Indian and southwestern Pacific sectors. A rotated empirical orthogonal function analysis reveals that the pattern of pointwise correlations found between the temperature reconstruction and SSTs is largely explained by the linear combination of three orthogonal modes of SST variability.

The thermal oceanographic signal of El Niño reconstructed from a Kiritimati Island coral

Central equatorial Pacific sea surface temperature (SST) anomaly is a critical predictor of basin‐wide oceanographic and atmospheric effects of the El Niño‐Southern Oscillation (ENSO) phenomenon. We employ two geochemical thermometers measured on coralline aragonite to reconstruct an independent proxy‐based measure of central equatorial Pacific sea surface temperature anomaly. In addition, we assess the observational error associated with extraction of large‐scale SST anomalies from δ18O and Sr/Ca measurements. On the basis of paired data for the 1981–1987 period, RMS error for the estimation of SST from Kiritimati coral δ18O is about 0.4°C, assuming no seawater δ18O influence; for Sr/Ca, the observational error is about 0.5°C. Singular spectrum analysis of the δ18O time series suggests that 1/3 of the variance is explained by SST anomaly and that this variance may be separated from other signals in the frequency domain. The interannual component of the δ18O record shares 70% variance with the interannual component of local SST anomaly estimates (ρ=−0.84) and correlates as highly with NINO3 region (150°W–90°W, 5°N–5°S) SST anomaly estimates; comparison of annual averages of the δ18O data with analyzed SST for 55 years suggests that the error in deriving annually averaged SST anomalies at Kiritimati is about 0.4°C. A global SST correlation analysis suggests significant correlation with the rest of the Pacific Basin and the tropical Indian and Atlantic sectors. The ocean‐wide level of correlation achieved using the coral data is indistinguishable from that achieved using the NINO3 SST anomaly index and suggests that a few well‐located coral reconstructions with low observational error may be sufficient to reconstruct the global SST anomaly field associated with ENSO activity.

Mixing in the ocean produced by tropical cyclones

Tropical cyclones induce entrainment in the upper ocean, and the associated mixing may cool the sea surface significantly. In this paper, the significance of mixing produced by tropical cyclones in the Atlantic is considered. Observed hydrography and tropical cyclone data are used to force an ocean model, which predicts changes in the temperature field due to wind-generated entrainment. The knowledge of the temperature field is used to translate the mixing into volume flow and heat flux, across isotherms. A calculation of the mean, cross isothermal volume flow produced by Atlantic tropical cyclones is presented. Tropical cyclones mix water in the temperature interval between 18 °C and 29 °C. Below 24 °C, the mixing moves water masses towards increasing temperature, and vice versa above 24 °C. The strength of this flow is about 1 × 10 6 m 3 s −1 . Turbulent heat-transport is associated with the mixing, and the diffusive heat-flux across the 24 °C isotherm is estimated to be 4 × 10 12 W. Feedback between tropical-cyclone activity and the area of surface water warmer than 26.5 °C is discussed. This feedback may attenuate large-scale sea-surface temperature anomalies, and its time-scale is estimated to be about 10 years DOI: 10.1034/j.1600-0870.1996.t01-1-00010.x

Modeling North Pacific SST anomalies as a response to anomalous atmospheric forcing

Large-scale sea surface temperature anomalies (SSTA) in the North Pacific ocean are often persistent for several months during wintertime. There is observational evidence that these patterns are forced by anomalous atmospheric circulation. Since the latter is in part related to the tropical El Niño/Southern Oscillation (ENSO) phenomenon it is hypothesized that part of the North Pacific SSTA's may be interpreted as remote oceanic response to anomalous equatorial Pacific SSTA's. Two experiments with a multi-level primitive equation model of the North Pacific have been conducted to study the influence of such anomalous atmospheric circulation on the SST. In both experiments anomalous wind stress as derived from the 1950–1979 COADS subset is specified as anomalous forcing. In experiment 1 no anomalous heat flux is introduced whereas in experiment 2 anomalous heat fluxes are estimated from anomalous surface winds and a simple advective atmosphere. In both experiments the GCM SSTA response are able to reproduce the main features of the time series of observed SSTA, in particular in winter. In experiment 1, however, the magnitudes are systematically too low. The addition of anomalous heat fluxes in experiment 2 significantly improves the simulation. The ENSO signal is clearly present in both simulations.

Stochastic forcing models of climate variability

Hasselmann (1976) has recently proposed a stochastic model of climate variability where climatic changes are caused by the intrinsic variability of the weather fluctuations. The complete atmosphere--ocean--cryosphere-land system is separated into long time scale cl imate components (mainly the ocean and the cryosphere) and short time scale wea ther components (mainly the atmosphere). The weather components exhibit stochastic fluctuations with a dominant t ime scale of a few days, reflecting instabilities of the atmospheric circulation. Because of their much larger time scale, the climate components respond essentially as integrators of the atmospheric forcing, which acts as an internal white noise generator. The random-walk climate fluctuations that develop have a variance which grows linearly with time, until feedback processes become important and lead eventually to a statistically stationary climate state. A red frequency spectrum is predicted for the climate variance, in general agreement with observations over a broad range of time scales, as reviewed below (see also Mitchell, 1976). The general theory is given in Hasselmann (1976). Here we shall introduce the formalism in the simpler context of sea surface temperature anomalies, and present new comparisons of the model predictions with observations in the North Pacific. It is shown that a single model reproduces the principal features and the seasonal variability of the large-scale sea-surface temperature anomalies observed in mid-latitudes. Other applications of the stochastic climate models are then reviewed. Quasi-geostraphic motions in the ocean interior and yearly and zonally averaged world temperature fluctuations induced by the natural variability of the atmosphere are discussed. The magnitude of

Pacific equatorial pressure gradient and Indian monsoon rainfall

SEA surface temperature (SST) anomalies are known to affect atmospheric flow patterns considerably. The Indian monsoon circulation is induced by the thermal contrast between the Asian continent and the Pacific and Indian oceans and by the orography of the Himalayas, so large scale SST anomalies are likely to affect the monsoon circulation, but after some time lag.