Average Sea Surface Temperature Anomalies Research Articles

Dynamical systems persistence parameter of sea surface temperature and its associations with regional averaged index over the tropical Pacific

AbstractDue to an index defined from regionally averaged sea surface temperature anomalies (SSTAs) unable to adequately characterize SSTA events, the dynamical persistence parameter was employed to infer more information than what the averaged SSTA index (SI) can capture from a new respect. By taking the whole SSTA field over a specific region as a dynamical system, was calculated to infer more (such as SSTA gradient) than SI. Moreover, the values of can provide the persistence information, low for long‐lasting SSTA events with well‐defined spatial patterns and high for transient behaviours. Globally, and SI can be taken as approximately orthogonal, but locally there are distinct associations between them. Detailed studies found that there are three kinds of origins for this global independence: alternating strong negative and positive correlation during extreme events, independence under the neutral conditions and low correlation caused by the inability of SI to the marked SSTA gradient. All above findings improve the understanding on the physical indications of and indicate that the new metric is at least a good supplement to the SSTA indices based on the regional average.

Multistep-Ahead Prediction of Ocean SSTA Based on Hybrid Empirical Mode Decomposition and Gated Recurrent Unit Model

The prediction of sea surface temperature anomalies (SSTA) is vital to the study of marine ecosystems and global climate. The SSTA can be accurately forecasted one step ahead by numerical and statistical methods. However, multi-step-ahead forecasting for SSTA is greatly challenging since the nonlinearity and non-stationarity of SSTA and the lag problem of prediction. Therefore, in this paper, a multi-step-ahead SSTA forecasting method based on the hybrid empirical mode decomposition (EMD) and gated recurrent unit (GRU) model is proposed considering that EMD has the advantage of reducing data complexity and GRU is good at long-term prediction of data. First, the EMD algorithm is applied to obtain several intrinsic modal mode functions (IMFs) that are more stationary than the original data. Then GRU is used for multi-step forecasting, in which three multi-step forecasting strategies (recursive, direct, and multi-output) are compared. The proposed hybrid model is validated by multi-step forecasting for monthly average SSTA at the Niño3.4 region. The experimental results show that using reconstruction error as part of the prediction effectively improves the prediction accuracy of the EEMD-GRU model and outperforms other EMD algorithms combined with GRU. Compared with traditional models, the EEMD-GRU model can better predict future multi-month trends of SSTA and effectively alleviate the problem of prediction lag of the traditional model. Finally, this model is applied to the Niño3.4 regional SSTA prediction, and the results show that this model can provide a reference for ocean research.

Changing relationship between La Niña and tropical cyclone landfalling activity in South China (La Niña and TC landfalling activity in South China)

ABSTRACTThis study investigates the effect of El Niño–Southern Oscillation and Indo‐Pacific warm pool sea‐surface temperature (SST) on tropical cyclone (TC) landfalling activity along the South China coast and develops a scheme for predicting this activity. In general, landfalling activity tends to be suppressed in El Niño years but a large uncertainty is found for La Niña years. Landfalling activity is generally enhanced in La Niña years before 1997 but suppressed in those after 1997, which may be related to the changes in TC frequency and track pattern over the western North Pacific (WNP) as well as the northward shift in genesis locations. The Indo‐Pacific warm pool SST is found to be related to the TC activity over the WNP and an SST index, defined as the average SST anomalies over the North Indian Ocean and the sea near the Philippines, is used to represent this anomaly. A significant warming of the Indo‐Pacific warm pool is found in the recent decade. The temperature change of this warm pool appears to modulate the TC activity over the WNP and TC landfalling activity in South China in a La Niña year, with an enhancement (a suppression) of TC activity if a cooling (warming) is found. This difference is related to the changes in the strength of monsoon trough, vertical wind shear and steering flow pattern. Based on these results, a schematic prediction scheme of landfalling activity in South China is proposed. Landfalling activity is likely to be normal or below normal if an El Niño event is expected to develop during the TC season. If a La Niña event is expected, and the predicted state of the Indo‐Pacific warm pool (obtained using the persistence forecast) shows a warming (cooling), landfalling activity is likely to be normal or below normal (above normal).

Changes in local oceanographic and atmospheric conditions shortly after the 2004 Indian Ocean tsunami

This study examines changes in the local oceanographic and atmospheric conditions over the southern Bay of Bengal and adjacent Indian Ocean waters after the 2004 Indian Ocean tsunami based on satellite remote sensing data and atmospheric reanalysis fields. After the tsunami that occurred on 26 December 2004, the accumulated rainfall had a notably increase (600 mm per month) in January of 2005 over deep waters to the southeast of Sri Lanka. This rainfall increase after the tsunami was accompanied with cooling in the sea surface temperature (SST) (up to −2 °C). Four-day averaged SST anomalies had a noticeable increase (1–4 °C) after the tsunami over the deep waters to the southwest of the epicenter. Series of ocean atmospheric and biological variables changed successively after the change of SST. The chain of causality between the tsunami and the changes in the local atmospheric conditions is suggested.

Impact of eastern equatorial Indian ocean during positive tropical dipole on regions over Tamilnadu and coastal Andhra Pradesh

The main objective of the present work is to investigate the influence of eastern Sea surface temperature (SST) anomalies during the Positive Tropical Indian Ocean dipole (PTIOD) events on regional summer monsoon rainfall especially over Tamilnadu and Coastal Andhra Pradesh (A. P.) for the period of 1980-2009. There were 7 strong PTIOD events recorded during the period of study which are accompanied by significant increase in the seasonal summer monsoon rainfall over India. Averaged SST anomalies (SSTA) over the EQ.ESIO (Equatorial Eastern South Indian Ocean) during AMJ (April, May, June) shows that colder (warmer) EQ.ESIO during AMJ and positive TIOD events were associated with the decreasing (increasing) tendency of summer monsoon rainfall over Tamilnadu and coastal A.P. The statistical analysis shows the correlation coefficient of 0.59 and 0.79 between AMJSST anomalies and the rainfall over Tamilnadu and Coastal A. P. respectively. Wind anomalies during PTIOD years with negative AMJSSTA, transports the cold upwelled oceanic current off Sumatra-Java towards the South West Bay of Bengal (SWBOB) and caused anomalous SST cooling in the region. Thus, the low level southerly wind reaching over the SWBOB during AMJ enforced the colder oceanic surface temperature of the region during the month of maximum solar insolation and thereby weak thermal gradient was observed with the shifting of the convective activity towards the south-east/northern Bay of Bengal (BOB). Moreover, less moisture advection with less convective activity in SWBOB region during pre-monsoon season may be the caused of the below-normal rainfall over Tamilnadu and coastal A. P. sub-divisions during June, July, August and September (JJAS)

Sea Surface Temperature Anomalies at the Mediterranean Coast of Turkey (Period of 1968-2010)

The purpose of the study is to review the sea surface temperature (SST) anomalies at the Mediterranean coast of Turkey during the period between 1968 and 2010. The SST data of the meteorology stations in Fethiye, Finike, Antalya, Alanya, Anamur, Mersin and Iskenderun are used for the study. According to this have the SST anomalies presented significant changes in annual and seasonal terms during the reviewed period. The most important parameter which affected the SST anomalies in annual and seasonal terms is the weather temperature. It can be said that also the changes in the NCP has an influence at a definite degree during the winter and spring seasons in annual terms. But NAO, ENSO, sunspots and precipitation are not much direct determinants for SST anomalies. The SST anomaly values have presented a symmetric distribution in Fethiye, Antalya and Anamur stations and an asymmetric distribution at the other stations in terms average deviation; and a symmetric distribution in Antalya station and an asymmetric distribution at the other stations in terms standard deviation. The annual average SST anomalies have shown an increase for all stations during the reviewed period. In terms of seasons have the SST anomalies presented an increase trend at all stations during summer, autumn and winter and a decrease trend in Fethiye, Antalya and Alanya stations and an increase trend all other stations during spring.

Forecast Skill and Predictability of Observed Atlantic Sea Surface Temperatures

Abstract An empirical statistical model is constructed to assess the forecast skill and the linear predictability of Atlantic Ocean sea surface temperature (SST) variability. Linear inverse modeling (LIM) is used to build a dynamically based statistical model using observed Atlantic SST anomalies between latitudes 20°S and 66°N from 1870 to 2009. LIM allows one to fit a multivariate red-noise model to the observed annually averaged SST anomalies and to test it. Forecast skill is assessed and is shown to be O(3–5 yr). After a few years, the skill is greatly reduced, especially in the subpolar region. In the stable dynamical system determined by LIM, skill of annual average SST anomalies arises from four damped eigenmodes. The four eigenmodes are shown to be relevant in particular for the optimal growth events of SST variance, with a pattern reminiscent of the low-frequency mode of variability, and in general for the predictability and variability of Atlantic SSTs on interannual time scales. LIM might serve as a useful benchmark for interannual and decadal forecasts of SST anomalies that are based on numerical models.

Comparing Twentieth- and Twenty-First-Century Patterns of Interannual Precipitation Variability over the Western United States and Northern Mexico*

Abstract The ability of coupled climate models to simulate the patterns of interannual precipitation variability over the western half of the United States and northern Mexico is investigated by applying principal component analysis to observations and model output. Global Precipitation Climatology Centre (GPCC) observations are compared to the pooled twentieth-century warm- and cold-season precipitation averages simulated by five coupled global climate models included in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The pooled model spatial structures (EOFs) closely match those of the GPCC observations for both halves of the year. Additionally, the twenty-first-century model pooled EOFs are almost identical in spatial extent and amplitude to their twentieth-century counterparts. Thus, the spatial characteristics of large-scale precipitation variability in the western United States are not projected to change in the twenty-first century. When global observed and modeled seasonally averaged sea surface temperature anomalies are correlated with the time series corresponding to the three leading EOFs to discern sources of each mode of precipitation variability, a pattern reminiscent of El Niño is found to be the only significant association. The spatial structures of variability also appear independent of the model-predicted precipitation trend over the twenty-first century, indicating that the mechanisms responsible for the trend are different from those associated with interannual variability. The results of this study lend confidence in the pooled model predictions of seasonal precipitation patterns, and they suggest that future changes will primarily result from the contribution of the mean trend over which statistically stationary interannual variability is superimposed.

Multidecadal Warming and Shoaling of Antarctic Intermediate Water*

Abstract Antarctic Intermediate Water (AAIW) is a dominant Southern Hemisphere water mass that spreads from its formation regions just north of the Antarctic Circumpolar Current (ACC) to at least 20°S in all oceans. This study uses an isopycnal climatology constructed from Argo conductivity–temperature–depth (CTD) profile data to define the current state of the AAIW salinity minimum (its core) and thence compute anomalies of AAIW core pressure, potential temperature, salinity, and potential density since the mid-1970s from ship-based CTD profiles. The results are used to calculate maps of temporal property trends at the AAIW core, where statistically significant strong circumpolar shoaling (30–50 dbar decade−1), warming (0.05°–0.15°C decade−1), and density reductions [up to −0.03 (kg m−3) decade−1] are found. These trends are strongest just north of the ACC in the southeast Pacific and Atlantic Oceans and decrease equatorward. Salinity trends are generally small, with their sign varying regionally. Bottle data are used to extend the AAIW core potential temperature anomaly analysis back to 1925 in the Atlantic and to ~1960 elsewhere. The modern warm AAIW core conditions appear largely unprecedented in the historical record: biennially and zonally binned median AAIW core potential temperatures within each ocean basin are, with the notable exception of the subtropical South Atlantic in the 1950s–70s, 0.2–1°C colder than modern values. Zonally averaged sea surface temperature anomalies around the AAIW formation latitudes in each ocean and sectoral southern annular mode indices are used to put the AAIW core property trends and variations into context.

The influence of sea surface temperature anomalies on low-frequency variability of the North Atlantic Oscillation

The influence of sea surface temperature anomalies (SSTA) on multi-year persistence of the North Atlantic Oscillation (NAO) during the second half of the twentieth century is investigated using the Center for Ocean-Land-Atmosphere Studies (COLA) Atmospheric GCM (AGCM) with an emphasis on isolating the geographic location of the SSTA that produce this influence. The present study focuses on calculating the atmospheric response to the SSTA averaged over 1988-1995 (1961-1968) corresponding to the observed period of strong persistence of the positive (negative) phase of the decadal NAO. The model response to the global 1988-1995 average SSTA shows a statistically significant large-scale pattern characteristic of the positive phase of the NAO. Forcing with the global 1961-1968 average SSTA generates a NAO of the opposite polarity compared to observations. However, all large-scale features both in the model and observations during this period are weaker in magnitude and less significant compared to 1988-1995. Additional idealized experiments show that over the northern center of the NAO the non-linear component of the forced response appears to be quite important and acts to enhance the positive NAO signal. On the other hand, over the southern center where the model response is the strongest, it is also essentially linear. The 1988-1995 average SSTA restricted to the western tropical Pacific region produce a positive NAO remarkably similar in structure but stronger in magnitude than the model response to the global and tropical Indo-Pacific 1988-1995 forcing. A 200-hPa geopotential height response in these experiments shows a positive anomaly over the southern center of the NAO embedded in the Rossby wave trains propagating from the western tropical Pacific. Indian Ocean SSTA lead to much weaker positive NAO primarily through the effect on its northern center. SST forcing confined to the North Atlantic north of equator does not produce a response statistically different from the control simulation, suggesting that it is not strong enough to significantly affect the phase of the decadal NAO. Inclusion of the South Atlantic north of 45° south does not change this result.

Value of operational forecasts of seasonal average sea surface temperature anomalies for selected rain-fed agricultural locations of Chile

This study investigates the economic value of several simple forecasts of 3-month average eastern tropical Pacific sea surface temperature anomalies (SSTA). Two Chilean agricultural regions were selected and the value of information for the main crops is obtained using an integrated model. The value of perfect forecasts is computed along with several simply formulated imperfect seasonal forecasts using a classification of the sea surface temperature anomalies in the equatorial Pacific. The main relationships between the accuracy of the forecasts and the economic benefits that can be obtained by using sea surface temperature forecasts are presented.

インド域の循環パターンによるエルニーニョ期間中の赤道東太平洋

This study investigates the relationship between circulation anomalies over India during the month of April, and sea surface temperature (SST) anomalies of the eastern Pacific Ocean (Niño 3 region). It is found that rain over northern parts of India and position of 500hPa ridge at 75°E, respectively, have significant correlation coefficients with subsequent SST anomalies of eastern Pacific Ocean (Niño 3 region). Moreover, these relationships are stronger during El Niño years. Since, during El Niño years, peak warming in SST occurs during October-December months, it could well be assessed with the help of these two parameters with the lead time of six months, once occurrence of an El Niño event is indicated by already existing dynamical models. To predict the peak warming during the El Niño years, data of April rain and position of 500hPa April ridge for eleven El Niño years, (1951, 1953, 1957, 1965, 1969, 1972, 1976, 1982, 1987, 1992, 1997) were subjected to the principal component analysis. First principal component was used to predict the average SST anomalies of October-December months through a simple regression equation using cross validation method. The standard deviation of average SST anomalies of October-December months for these eleven years is 0.96, while the root mean square error of the predicted value is 0.52, which is indicative of the good skill of prediction.

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.

The Coupled Patterns between Sea Level Pressure and Sea Surface Temperature in the Midlatitude North Atlantic

Abstract Monthly variability of atmosphere-ocean interactions in the midlatitude North Atlantic during the winter months (November–April) is examined. Composite and singular value decomposition (SVD) analyses are applied to the observed sea level pressure (SLP) and sea surface temperature (SST) anomalies of each winter month for the period 1950–1987. The SLP anomaly composites (i.e., SLP differences between selected warm and cold SST months) are constructed based on the averaged SST anomalies over the RM region (60°–40°W and 50°–40°N). These composites shift from a positive monopole pattern in early winter to a dipole pattern in midwinter and then back to a monopole pattern in late winter. A complementary SVD analysis reveals that the first SVD mode is dipole structured and especially dominant in midwinter. The second SVD mode is monopole featured and more dominant in early and late winter than in midwinter. By examining the spatial distributions of the SVD modes and especially their similarities to the p...

RELATIONSHIP OF AIR TEMPERATURES IN NEW ZEALAND TO REGIONAL ANOMALIES IN SEA-SURFACE TEMPERATURE AND ATMOSPHERIC CIRCULATION

A study has been made of the relationship of New Zealand national-mean air temperature anomalies to regional circulation anomalies (represented by circulation indices), regional average sea-surface temperature anomalies, and the SOI. Partly this was to determine the role of these factors during 1992, which was the coldest year for nearly 50 years. The patterns of large-scale anomalies of regional circulation and SST during the year are described. Correlation analysis was performed on 1950–1993 monthly data filtered into two series to separately represent the monthly and interannual time-scales. National air temperatures and regional mean SST were found to vary in closely similar fashion, with maximum correlation coefficients of 0·60 and 0·87 for the high- and low-frequency series respectively. For the high-frequency series, SST lagged air temperature by half a month and had amplitudes less than half those of air temperature. From an examination of the lags, amplitudes, and maps of pressure and SST anomalies, we conclude, firstly, that the dominant influence on both the air and sea-surface temperatures is the meridional circulation (southerly anomalies resulting in low temperatures), and secondly, that SST anomalies are not a primary cause of national-mean air temperature anomalies at the monthly scale. An oscillation of about 6-month period, which is present in all the high-frequency series, was especially evident during 1991–1993 (with an amplitude of about 1·2°C in air temperature). In the case of the low-frequency series, regional SST lagged national air temperature by 1–2 months and had amplitudes nearly equal to those of air temperature. Both were well correlated with the meridional circulation and the SOI. The 1992 air temperatures were depressed mainly because of the anomalous southerly airflow, which was associated with the prevailing ENSO episode, together with some impact of the Mt Pinatubo eruption. Our results provide good post hoc explanations, but they do not offer much potential for prediction at the monthly-to-seasonal scale, apart from whatever possibilities might result from a better understanding of the quasi-6-month oscillation.

Simulation and Predictability in a Coupled TOGA Model

A model of the tropical ocean and global atmosphere is described. It consists of an aqua-planet form of version one of the NCAR Community Climate Model coupled to a primitive equation model for the upper tropical ocean in a rectangular basin. At 24-year simulation is described that has almost no climate drift, a good simulation of the mean temperature gradient across the ocean, but smaller than observed annual and interannual variability. The coupled model is analyzed to see where it occurs on the schematic bifurcation diagram of Neelin. In years 9-16 of the simulation there is a dominant oscillation with a period of two years. The spatial pattern of this oscillation shows up clearly in the first empirical orthogonal function calculated from monthly averages of sea surface temperature anomalies. A series of 19 model-twin predictability out to a year. The predictability times are marginally increased if only the coefficient of the first empirical orthogonal function of monthly averaged sea surface temperature anomalies or NINO3 sea surface temperature is predicted. There is some evidence to indicate that it is easier to predict the onset of a model warm event than to predict the onset of a model cold event. More detailedmore » analysis of the first model-twin experiment shows that the initial divergence in the integrations is a change at day 6 in the incoming solar radiation due to a change in the atmospheric model clouds. The dominant early change in sea surface temperature occurs by this change in radiative heat flux. If the cloud feedback is set to zero, then the first changes are delayed to day 12 and occur in the evaporative and sensible heat fluxes and in the atmospheric wind stress. In this case the dominant early change to sea surface temperature is by advection due to the changed wind stress. 16 refs., 55 figs.« less