Cycle Of Sea Surface Temperature Research Articles

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983–2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

The emerging human influence on the seasonal cycle of sea surface temperature

The emerging human influence on the seasonal cycle of sea surface temperature

The phase change in the annual cycle of sea surface temperature

In recent decades, many research efforts focused on global climate change, multidecadal, decadal, interannual variability, and the increasing extreme events of sea surface temperature. In contrast, the continuous evolution of the reference frame, the annual cycle of SST used to quantify the aforementioned variability and changes, has long been overlooked, resulting in difficulties in understanding the underlying physical mechanisms responsible for these variability and changes. In this study, we strive to bridge this gap on the phase changes in SST annual cycle. By devising a running correlation-based method, we can now quantify the non-sinusoidal shape of the evolving SST annual cycle, such as the advancing or delaying of summer and winter peaking times. It is revealed that the varying phases of summer or winter are more closely linked to multidecadal SST variability than to long-term climate change. Both the systematic shift of the phase and alterations in the annual cycle shape contribute to the phase changes, which explain 0.4~1.0 °C of monthly SST anomaly with respect to the climatological annual cycle in a multidecadal timescale. Furthermore, it is evident that the SST phases in historical simulations are better captured in winter than in summer and exhibit stronger variation compared with observation.

The effect of diurnal warming of sea‐surface temperatures on the propagation speed of the Madden–Julian oscillation

AbstractThe diurnal warm layer in the upper ocean develops during low surface winds and high incoming solar radiation conditions, often increasing sea‐surface temperatures (SSTs) by up to 1°C. The suppressed phase of the Madden–Julian Oscillation (MJO) favours the formation of such a layer. Here, we analyse the coupled ocean–atmosphere and atmosphere‐only numerical weather prediction systems of the UK Met Office to reveal that important differences arise from the representation of the diurnal warm layer in the coupled model. Though both models are skilful in predicting the MJO to at least a 7‐day lead time, the coupled model predicts approximately 12% faster MJO RMM phase speed propagation than the atmosphere‐only model due to the ability to resolve diurnal warming in the upper ocean that rectifies onto MJO‐associated SST anomalies. The diurnal warming of SST (dSST) in the coupled model leads to an increase in daily mean SST compared with the atmosphere‐only model persisted foundation SST. The strength of the dSST in the coupled model is modulated by MJO conditions. During suppressed MJO conditions on lead day 1, the dSST is enhanced, leading to 0.2°C warmer daily mean MJO‐associated SST anomalies and increased convection in the coupled model by lead day 7. During active MJO convection, the dSST is suppressed, leading to 0.1°C colder MJO‐associated SST anomalies in the coupled model and reduced convection by lead day 7. This variability in dSST further amplifies the MJO propagation speed, underlining the importance of the two‐way feedback between the MJO and the diurnal cycle of SST and the need to accurately represent this process in coupled models.

A 50-year cycle of sea surface temperature regulates decadal precipitation in the tropical and South Atlantic region

Northeast Brazil and Western Africa are two regions geographically separated by the Atlantic Ocean, both home to vulnerable populations living in semi-arid areas. Atlantic Ocean modes of variability and their interactions with the atmosphere are the main drivers of decadal precipitation in these Atlantic Ocean coastal areas. How these low-frequency modes of variability evolve and interact with each other is key to understanding and predicting decadal precipitation. Here we use the Self-Organizing Maps neural network with different variables to unravel causality between the Atlantic modes of variability and their interactions with the atmosphere. Our study finds an 82% (p<0.05) anti-correlation between decadal rainfall in Northeast Brazil and Western Africa from 1979 to 2005. We also find three multi-decadal cycles: 1870-1920, 1920-1970, and 1970-2019 (satellite era), pointing to a 50-year periodicity governing the sea surface temperature anomalies of Tropical and South Atlantic. Our results demonstrate how Northeast Brazil and Western Africa rainfall anti-correlation was formed in the satellite era and how it might be part of a 50-year cycle from the Tropical and South Atlantic decadal variability.

Revisiting the effect of increasing horizontal resolution on the evolution of El Niño in a coupled model

The ENSO (El Niño southern oscillation) in the tropical Pacific plays a crucial role in regulating the Indian summer monsoon. Many mechanisms have been proposed to explain the positive and negative feedback associated with the ENSO through air-sea interaction in the tropical Pacific. Historical run data at varying oceanic and atmospheric resolutions from the MPI-ESM model is analyzed and compared with observations to determine the possible reasons for the much earlier onset and delayed withdrawal of ENSO in the coupled model. Increasing the resolution of the oceanic and atmospheric components of the coupled model helps in well-resolving the annual cycle of sea surface temperature in the tropical Pacific. There is a significant improvement in the early onset and late withdrawal of El Niño in the coupled model with increasing horizontal resolution of the model components. The weak subsurface propagation along the 20 °C isotherm in the equatorial Pacific improves on increasing the horizontal resolution of the coupled model. Similar to observations, there is a clear eastward extension of convection, 20° east of the dateline, in the equatorial tropical Pacific in the coupled model during ENSO years. Increasing the resolution of the oceanic and atmospheric components of the coupled model improves the simulation of convective activity over the western Pacific along with the improved magnitude of anomalous zonal wind strength during El Niño years. However, the presentation of convective activity over the equatorial Pacific deteriorated on increasing atmospheric resolution further to T255 due to the enhanced value of the interannual amplitude of intraseasonal zonal wind around the international dateline. Also, the coupled model does not capture the accurate eastward propagation of the Madden Julian Oscillation envelope over the western Pacific. While higher resolutions showed improvement in the representation of El Niño events in terms of their number and duration, challenges persisted in accurately capturing the frequency of these events and their related triggering mechanisms. Understanding the intricate interplay of factors influencing the evolution of El Niño requires further research and progress in modeling strategies.

Triple-dip La Niña in 2020–23: understanding the role of the annual cycle in tropical Pacific SST

The triple-dip La Niña in 2020–23 is characterized by persisting southeasterly wind anomalies over the tropical central and eastern Pacific. Our results show that the wind anomalies are associated with the anomalously negative phase of the first two leading modes of the annual cycle (antisymmetric and symmetric modes about the equator) of sea surface temperature (SST) in the tropical Pacific. The two modes account for 82.2% and 13.5% of the total variance, linking to the seasonal swing of SST between the northern and southern hemispheres and the temporal evolution of El Niño-Southern Oscillation, respectively. During 2020–23, the persistently and anomalously negative phase of the symmetric mode enhances easterly wind over the tropical central Pacific, while the antisymmetric mode strengthens the southeasterly wind over the tropical eastern Pacific. The anomalously negative phase of the antisymmetric mode is associated with the contrast of SST anomalies between the northern and southern hemispheres, which provided a favorable background for the triple-dip La Niña in 2020–23.

40 years of changes in sea surface temperature along the Western Iberian Coast

Climate change is causing mean sea surface temperatures (SST) to increase worldwide. However, this increase has not been temporally or spatially uniform, with variations observed depending both on the period considered and the geographic region. In this context, this paper aims to quantify relevant changes in SST along the Western Iberian Coast over the last four decades, through the calculation of trends and anomalies of long-term time series of in situ observations and satellite-derived data. Potential drivers of SST changes were considered using atmospheric and teleconnections time series. Changes in the seasonal cycle of SST were also evaluated.We show that SST has increased since 1982, with regional variations between 0.10 and 0.25 °C per decade, with an increase in air temperature appearing to drive the SST trends along the Iberian coast. In the near-shore area, no significant trends or changes in the seasonal cycle of SST were observed, which is likely due to a buffer effect caused by the seasonal upwelling that characterizes the region. Recent decades show a slowdown in the increase rate of SST along the Western Iberian Coast. An upwelling intensification could justify this observation, along with the effect of teleconnections on the regional climate, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation Index (WeMOI). Our results suggest that the WeMOI plays a more important role in coastal SST variability than the other teleconnections.The present study quantifies regional changes in SST and enhances knowledge of the role of ocean-atmosphere interactions in regulating climate and weather conditions. Moreover, it provides a relevant scientific context to the development of regional adaptative and mitigation actions in response to climate change.

The Impacts of a Weakened Atlantic Meridional Overturning Circulation on ENSO in a Warmer Climate

AbstractThis study quantifies the impacts of the Atlantic Meridional Overturning Circulation (AMOC) on the El Niño–Southern Oscillation (ENSO) under anthropogenic warming by comparing climate change model simulations with declining and fixed strengths of the overturning. After the 1980s, a weakened AMOC is shown to reduce the strength of the annual cycle of sea surface temperature (SST) in the eastern equatorial Pacific and induce anomalous cross‐equatorial northerly winds there, which strengthens ENSO variability by about 11%. An analysis of the Bjerknes stability index reveals that this intensification of ENSO results mainly from enhanced Ekman upwelling feedback due to amplified atmospheric wind response to SST anomalies and oceanic upwelling response to equatorial wind stress anomalies. The weakened AMOC also promotes the occurrence of Central Pacific El Niño events and reduces ENSO skewness. These AMOC impacts on ENSO magnitude and complexity throughout the twenty‐first century are however smaller than ENSO variations expected from internal climate variability.

Seasonal cycle of sea surface temperature in the tropical Angolan Upwelling System

Abstract. The Angolan shelf system represents a highly productive ecosystem. Throughout the year the sea surface is cooler near the coast than further offshore. The lowest sea surface temperature (SST), strongest cross-shore temperature gradient, and maximum productivity occur in austral winter when seasonally prevailing upwelling-favourable winds are weakest. Here, we investigate the seasonal mixed layer heat budget to identify atmospheric and oceanic causes for heat content variability. By using different satellite and in situ data, we derive monthly estimates of surface heat fluxes, mean horizontal advection, and local heat content change. We calculate the heat budgets for the near-coastal and offshore regions separately to explore processes that lead to the observed SST differences. The results show that the net surface heat flux warms the coastal ocean stronger than further offshore, thus acting to damp spatial SST differences. Mean horizontal heat advection is dominated by meridional advection of warm water along the Angolan coast. However, its contribution to the heat budget is small. Ocean turbulence data suggest that the heat flux, due to turbulent mixing across the base of the mixed layer, is an important cooling term. This turbulent cooling, being strongest in shallow shelf regions, is capable of explaining the observed negative cross-shore temperature gradient. The residuum of the mixed layer heat budget and uncertainties of budget terms are discussed.

Mid-Holocene expansion of the Indian Ocean warm pool documented in coral Sr/Ca records from Kenya

Proxy reconstructions suggest that mid-Holocene East African temperatures were warmer than today between 8 and 5 ka BP, but climate models cannot replicate this warming. Precessional forcing caused a shift of maximum insolation from boreal spring to fall in the mid-Holocene, which may have favored intense warming at the start of the warm season. Here, we use three Porites corals from Kenya that represent time windows from 6.55 to 5.87 ka BP to reconstruct past sea surface temperature (SST) seasonality from coral Sr/Ca ratios in the western Indian Ocean during the mid-Holocene. Although the Indian monsoon was reportedly stronger in the mid-Holocene, which should have amplified the seasonal cycle of SST in the western Indian Ocean, the corals suggest reduced seasonality (mean 3.2 °C) compared to the modern record (mean 4.3 °C). Warming in austral spring is followed by a prolonged period of warm SSTs, suggesting that an upper limit of tropical SSTs under mid-Holocene conditions was reached at the start of the warm season, and SSTs then remained stable. Similar changes are seen at the Seychelles. Bootstrap estimates suggest a reduction in SST seasonality of 1.3 ± 0.22 °C at Kenya and 1.7 ± 0.32 °C at the Seychelles. SST seasonality at Kenya corresponds to present-day SST seasonality at 55° E–60° E, while SST seasonality at the Seychelles corresponds to present day SST seasonality at ~ 65° E. This implies a significant westward expansion of the Indian Ocean warm pool. Furthermore, the coral data suggests that SST seasonality deviates from seasonal changes in orbital insolation due to ocean–atmosphere interactions.

Role of Ocean-Atmosphere Interface in Annual and Semiannual SST Cycles in the Indian Ocean

A long-term analysis of temperature can be used to describe the main mechanisms that operate at the surface of the ocean. The average sea surface temperature (SST) contour plots for the Indian Ocean are produced based on the World Ocean Atlas Data Set (1994). SST, together with the independent variables wind (Wx, zonal component of pseudo-stress wind and Wy, meridional component of pseudo-stress wind), net-down-fresh-water-flow (NDFF), and Ekman pumping, are included in a multiple regression analysis to define the relative importance of each one of these variables in the physical processes at the surface of the Indian Ocean. The NDFF data set is based on COADS (Comprehensive Ocean-Atmosphere Data Set). The wind data is obtained from the Florida State University (FSU). The harmonic terms of the variables are calculated, which is considered to be stationary and expressed by a Fourier series as a cosine function. The harmonic terms are multiplied by the maximum amplitude of the variables and then added to their mean annual values. The isotherms are mainly meridional along the western boundary, but zonal in the southern Indian Ocean. The annual component is seen to have a maximum in July, Summer Monsoon (SW Monsoon) and a minimum in January, during the Winter Monsoon (NE Monsoon). The amplitude of the semiannual component is smaller, with two maxima in May and October and two minima in February and August. The small magnitude of these residuals errors is an indication that the temperature variability during this period and for this area can be explained reasonably well by the two harmonic terms. In the Arabian Sea, the final regression equations for SST variability show that it is mainly affected by the Wx, Ekman pumping and NDFF. For most of the areas of the Bay of Bengal, as well as for most of the locations in the southern tropical Indian Ocean, the entered independent variables can explain SST. Two components fit to observation can be used to predict SST together with the regression equations. Although harmonic analysis can be used to study SST variability, a multiple regression analysis is required to identify and quantify the variables related to areas of large annual and semiannual variability. Different techniques are therefore used together to provide more reliable results in SST configuration in the Indian Ocean.

Seasonal and intra-seasonal variations of surface hydrological parameters over North Yellow Sea and its implications for applicability of quasi-synchronous ship-based multi-station hydrological investigation data

The quasi-synchronous ship-based multi-station hydrological investigation is the most basic and classic oceanographic research method. Nevertheless, the temporal variability of regional hydrological parameters raises the uncertainty of interpreting quasi-synchronous multi-station datasets. There has been a lack of in-depth assessment of the accuracy of survey results. In this study, two hydrological investigations during the summer of 2016 and winter of 2017 in the North Yellow Sea (NYS), accompanied by time series buoy observations, are presented to elucidate its influencing factors and applicability evaluation of cruise hydrological investigation data. The results indicate that the solar radiation and tidal condition account for the diurnal and semi-diurnal cycle of sea surface temperature (SST) in the summer and winter seasons, respectively. The sea surface salinity shows no significant variation during the cruise survey period, while the seasonal characteristic is dominated by the regional ocean circulation. The vertical hydrological structures (stratified in summer or well-mixed in winter) limit or enhance the upward diffusion of bottom resuspended sediment in the offshore area, furtherly causing higher surface turbidity in winter. The upwelling phenomenon is underestimated in summer cruises due to the diurnal variation of SST, while the cold-water tongue may be overinterpreted in winter cruise because of the northerly wind event. The applicability of multi-station hydrological investigation data depends on the comparison of the spatio-temporal scale of the scientific question being studied with the time-varying of the data. The coefficient of variation (CV) of sea surface parameters ranges from 0.03 to 0.36 for SST, 0.02 to 0.04 for SSS, 0.01 to 1.37 for chl a, and 0.06 to 0.50 for Rrs_555. The sea surface parameters display higher variabilities during spring and autumn season than summer and winter season over NYS, and the coastal areas show larger temporal variation than central NYS. It is suggested that the multi-station investigation should be conducted at the time when the hydrological structure is relatively stable as far as possible, especially for the nearshore stations. This study provides a meaningful reference for oceanographic research that although the background hydrologic field can be well described through the ship-based investigation data, attention should also be paid to the influence of time-varying meteorological and hydrological conditions to achieve more objective data interpretation.

Planktonic foraminiferal assemblages and particle fluxes at the entrance of the Gulf of California highlight the effects of the strong El Niño 2015–2016

The impacts of El Niño 2015–2016 on planktonic foraminiferal assemblages and particle fluxes (total mass, organic carbon, total nitrogen, and carbonate) were analyzed in a sediment trap record located at the entrance of the Gulf of California from 2015 to 2019. Biweekly data of the sea surface temperature (SST) and sea surface chlorophyll-a (Chl-a) were obtained from satellite images (MODIS-AQUA) during this period. Particle fluxes and planktonic foraminiferal assemblages reflected the seasonal cycles of SST and phytoplankton biomass highlighting the effects of El Niño 2015–2016. During neutral and La Niña conditions, winter-spring upwelling leads to low SST, high Chl-a and particle fluxes, and an assemblage dominated by Globigerina bulloides while the summers are characterized by high SST, low Chl-a and particle fluxes, and a Globorotaloides hexagonus assemblage. In contrast, in normal summers, there is an alternation of G. bulloides and Orbulina universa-Trilobatus sacculifer-Globigerinella siphonifera associations. By late autumn under La Niña conditions, the Globigerinita glutinata assemblage reflects the transition from warm to cold conditions and the beginning of the upwelling season. This general pattern was affected by El Niño during 2015–2016. From late summer 2015 to early winter 2016 (El Niño 2015–2016 maximum intensity), Globigerinoides tenellus dominated, reflecting the intrusion of warm and oligotrophic equatorial waters. These results show the strong influence of El Niño Southern Oscillation (ENSO) on oceanic dynamics and planktonic foraminiferal assemblages at the entrance of the Gulf of California, and allow for a better interpretation of the preservation of these anomalous warm events in the sedimentary record, which can provide a better understanding of the long-term variations and effects of ENSO.

Weakening of Indian Summer Monsoon Synoptic Activity in Response to Polar Sea Ice Melt Induced by Albedo Reduction in a Climate Model

AbstractThe effect of polar sea ice melt on low latitude climate is little known. To understand the response of the Indian summer monsoon (ISM) synoptic activity to the sea ice melt, we have run a suite of coupled and uncoupled climate model simulations. In one set of simulations, the albedo of sea ice is reduced so that it would melt due to increased absorption of solar radiation. The coupled model simulation with a reduced sea ice albedo resulted in an almost complete melting of the sea ice in summer in both hemispheres. A high‐resolution (50 km) atmospheric general circulation model (AGCM) is forced with the climatological annual cycles of sea surface temperature (SST) and sea ice concentrations (SIC) from the coupled model outputs to better resolve synoptic scale variability. In the high‐resolution AGCM simulations forced with SST and SIC from the sea ice melt experiments, the ISM circulation weakened substantially, and the monsoon low‐pressure systems (LPS) activity experienced an overall decline of 23%, with a widespread weakening in the south and a moderate strengthening over the north, in response to a decline of 78% (24%) in SIC over the Arctic (Antarctic) in the June–September season. The changes in the LPS activity in response to polar sea ice melt are found to be mostly driven by the changes in low‐level absolute vorticity and vertical shear over the Bay of Bengal.

Monitoring the Seasonal Distribution and Variation of Sea Surface Temperature and Chlorophyll Concentration in Bay of Bengal using MODIS Satellite Images

Using MODIS Global Satellite products from 2016 to 2020, the variance in sea surface temperature (SST) and chlorophyll concentrations in the waters of the Bay of Bengal (BoB) is investigated during this study. Seasonal maps prepared from the monthly average of SST are compared to observe the change throughout the timeframes of spring, summer, autumn, and winter. The annual cycle of SST depicts the phases of cooling in winter, heating in summer, and warming in spring. It has been found that the presence of heated pools (SST > 30°C) prolongs the summer endurance within the Bay in summer. The SST variations are also strongly linked to regional-scale climate variations from late winter to early spring. Anomalies in chlorophyll are often considered early indicators and drivers of changes in marine resources. However, there has been little assessment of the abnormality in this component in coastal waters of the BoB. The measured chlorophyll distribution during the study reveals anomalies consistent in magnitude having a prominent north-south gradient, where the greater concentrations lie in the northern part. In addition, the fluvial input provided in the central part of the Bay by the Ganges-Brahmaputra-Meghna River system during monsoon contributes additional credence to this assertion.

Biases in sea surface temperature and the annual cycle of Greater Horn of Africa rainfall in CMIP6

AbstractClimatological rainfall across much of the Greater Horn of Africa has a bimodal annual cycle characterized by the short rains from October to December and the long rains from March to May. Previous generations of climate models from the Coupled Model Intercomparison Project (CMIP3 and CMIP5) generally misrepresented the bimodal rainfall distribution in this region by generating too much rainfall during the short rains and too little during the long rains. The peak of the long rains in these models also typically showed a pronounced 1‐month lag relative to observations. Here, the ability of 21 CMIP6 models to properly simulate the observed, climatological annual cycle of Greater Horn rainfall is examined, comparing results with CMIP5 and CMIP3. As previous work has shown a connection between Greater Horn climatological rainfall biases and model biases in sea surface temperatures (SSTs), pattern correlations of climatological SST biases are also analysed. For the multi‐model mean, it is found that the earlier biases in Greater Horn rainfall and associated SSTs persist in CMIP6. Examining only the three best performing models in each CMIP group reveals the CMIP6 models outperform those in CMIP3, with mixed results regarding improvements over CMIP5. For the best performing CMIP6 models, the SST and 850 hPa wind biases are reduced over the Indian Ocean relative to the other CMIP6 models examined. No statistically significant relationship was identified between CMIP6 model performance and the horizontal resolution of the model. Combined, these results indicate the importance of properly simulating the annual cycle of SSTs in order to successfully model the observed rainfall annual cycle in the Greater Horn.

Modulation of observed sea surface temperature variation by the quasi‐biweekly oscillation in the tropical western Pacific during boreal summer

AbstractUsing 17‐year in situ buoy observations, this study investigates how sea surface temperature (SST) over the tropical western Pacific Ocean is modulated by the quasi‐biweekly oscillation (QBWO) during boreal summer. The 10‐buoy mean phase‐by‐phase composites of SST indicate that SST evolution lags behind the convection cycle by approximately one quarter, with the maximum SST occurring in Phase −90° (29.68°C) and the minimum SST occurring in Phase 90° (29.37°C). The diurnal cycle of SST (dSST) is in phase with the convection cycle, with the minimum dSST occurring during the convectively active phase (0.34°C) and the maximum dSST occurring during the convectively suppressed phase (0.61°C). The fluctuation in the dSST reaches 0.27°C, which is similar to that in the SST (0.31°C). This kind of oscillation can be well explained by the evolution of the sea surface forcing parameters, especially the shortwave radiation and wind speeds, observed from the buoys. In addition, the composite range of the dSST suggests an interesting asymmetry between Phase −90° and 90°. The interaction of the background summer mean state and the 10–30‐day intraseasonal anomalies causes the asymmetry in wind speed between Phase −90° and 90°, which in turn results in the asymmetry in the dSST between these two phases. Since QBWOs are more likely to occur during El Niño developing summers than during El Niño decaying summers, the 10–30‐day intraseasonal SST and dSST variances during El Niño developing summers are stronger than those during El Niño decaying summers.

A Closer Look at Power-Law Scaling Applied to Sea Surface Temperature from Scripps Pier Using Empirical Mode Decomposition

AbstractThe purpose of this study is to extract more information about the scaling exponents we obtain from sea surface temperature (SST) because their information content is limited to a single value. We examine the application of empirical mode decomposition (EMD) to power-law scaling using SST from Scripps Pier, California. The daily observations we employ extend from 1920 to 2009, a period of 90 years. The annual cycle and the long-term trend were first removed. The decomposition produced a total of 15 modes. The scaling exponents were then calculated separately for each mode from the EMD. We have examined the distribution of scaling exponents with respect to the ensemble, and then with respect to the individual modes for the oceanic processes that we may infer from them. The first three modes are antipersistent and contain about one-quarter of the total variance. The pattern of modes that was obtained is continuous and relatively smooth beyond mode 3 with increasing values up to mode 8 and generally decreasing values thereafter. The pattern exhibits intramodal correlation, as expected, and intermodal correlation as well. Intermodal correlation is likely due, for the most part, to long-range persistence. The annual cycle in SST at Scripps Pier is a dominant feature in the record and contains almost 70% of the variance. A method for removing the annual cycle that is not based on removing the mean value is introduced and is recommended for future use.

Role of Indian Ocean in Influencing the Rainfall of Central India

The Indian summer monsoon as a major component of the global climate system has received renewed attention in recent years. There are many instances of years with floods (strong monsoon) or drought (weak monsoon) during which India as a whole receives excess or deficient seasonal rainfall, respectively. Monsoon variations, particularly if they are unanticipated, impart significant economic and social consequences. On the other hand, an accurate long-lead prediction of monsoon rainfall can improve planning to mitigate the adverse effects of the inter-annual variability of the monsoon. One such attempt is made in this research to establish empirical relationships between sea-surface temperature (SST) and summer monsoon rainfall over Central India. India is surrounded by Indian Ocean and the annual cycle of SST in the Indian Ocean is crucially important in the distribution of precipitation over the Indian subcontinent. The study identifies four pockets in the Indian Ocean which can be considered as precursors to summer monsoon rainfall. Correlation analysis with lags in months was carried out to establish association between the SST over these pockets and summer monsoon rainfall. The study revealed that the relationship between the two variables has undergone phase-change, and has oscillated between inverse and direct correlation values. Besides, the study also reveals the relationship between SST and monsoon rainfall for different meteorological subdivisions of Central India, which further broadens the scope for researchers to evaluate the impact of coupled land-ocean and air interactions for different micro-spatial units of India.