Intraseasonal Sea Surface Temperature Variability Research Articles

Bay of Bengal upper-ocean stratification and the sub-seasonal variability in convection: Role of rivers in a coupled ocean-atmosphere model

The Bay of Bengal (BoB) receives a large amount of freshwater from rains and rivers, resulting in large upper-ocean stratification due to the freshening effect. This salinity stratification has been theorized to impact sea-surface temperature (SST) and convection on intra-seasonal time scales by affecting the ocean mixed layer and the barrier layer. This article aims to quantify the impact of salinity stratification on the sub-seasonal variability in SST and convection by using in-situ ocean observations and coupled model experiments. It is shown that monsoon intra-seasonal oscillations (MISOs) exhibit varied levels of intra-seasonal variability in SST and rainfall based on the underlying ocean conditions. The largest intra-seasonal variability in SST does not cause the largest convection variability in the north-western BoB. Instead, moderate variability in SST and rainfall associated with MISOs co-occur with deep mixed layer and thick barrier layer conditions. Realistic representation of river freshwater fluxes in a coupled ocean-atmosphere model leads to improved intra-seasonal SST and rainfall variability. Thick barrier layers in the north-western Bay attenuates the entrainment cooling of the mixed layer, and the high mixed layer heat content provides conducive oceanic conditions for the genesis of monsoon low-pressure systems (LPS), thereby affecting rainfall over India. This study has important implications for operation forecasting using coupled models.

Climate Process Team: Improvement of Ocean Component of NOAA Climate Forecast System Relevant to Madden‐Julian Oscillation Simulations

AbstractGiven the increasing attention in forecasting weather and climate on the subseasonal time scale in recent years, National Oceanic and Atmospheric Administration (NOAA) announced to support Climate Process Teams (CPTs) which aim to improve the Madden‐Julian Oscillation (MJO) prediction by NOAA’s global forecasting models. Our team supported by this CPT program focuses primarily on the improvement of upper ocean mixing parameterization and air‐sea fluxes in the NOAA Climate Forecast System (CFS). Major improvement includes the increase of the vertical resolution in the upper ocean and the implementation of General Ocean Turbulence Model (GOTM) in CFS. In addition to existing mixing schemes in GOTM, a newly developed scheme based on observations in the tropical ocean, with further modifications, has been included. A better performance of ocean component is demonstrated through one‐dimensional ocean model and ocean general circulation model simulations validated by the comparison with in‐situ observations. These include a large sea surface temperature (SST) diurnal cycle during the MJO suppressed phase, intraseasonal SST variations associated with the MJO, ocean response to atmospheric cold pools, and deep cycle turbulence. Impact of the high‐vertical resolution of ocean component on CFS simulation of MJO‐associated ocean temperature variations is evident. Also, the magnitude of SST changes caused by high‐resolution ocean component is sufficient to influence the skill of MJO prediction by CFS.

A numerical study on the mixed layer depth variability and its influence on the sea surface temperature during 2013–2014 in the Bay of Bengal and Equatorial Indian Ocean

This study addresses the air–sea interaction processes and mixed layer variability, which cause the intraseasonal oscillations in the sea surface temperature (SST) during January 2013–December 2014 using the Regional Ocean Modeling System (ROMS). We have analyzed the SST variability at three locations—northern Bay of Bengal (BoB)/15°N, 90°E (R15), central BoB/12°N, 90°E (R12), and equatorial Indian Ocean (EIO)/0°N, 80.5°E (R0). During northeast monsoon (NEM) and southwest monsoon (SWM), intraseasonal SST variability is respectively controlled by the intense outgoing fluxes (sum of longwave radiation, latent heat flux, and sensible heat flux) and zonal wind stress. The intraseasonal SST variability in spring and fall is modulated by intense incoming shortwave radiation. There is a profound impact of mixed layer depth (MLD) variations on the intraseasonal SST oscillations in the BoB and EIO. At R15, and R12, deepened simulated MLD is associated with the lowered SST variability in the NEM and SWM. In spring and fall, the shallow MLD variability corresponds to higher intraseasonal SST variability at the buoy locations. In the northern BoB, ROMS cannot capture barrier layer (BL) and temperature inversion (TI) accurately in the winter and premonsoon season due to salinity bias, resulting in the difference between simulated and actual MLD. But the simulated MLD bias does not affect the intraseasonal SST structures in the NEM and pre-SWM. In the northern BoB, the proper representation of salinity structure may represent BL, TI, and MLD, accurately in the simulation during the winter and premonsoon season.

Rectification of the Intraseasonal SST Variability by the Diurnal Cycle of SST Revealed by the Global Tropical Moored Buoy Array

AbstractIt has been suggested that the intraseasonal sea surface temperature (SST) variability in the tropical oceans can be amplified by the diurnal cycle of SST (dSST). Here, by analyzing the global tropical moored buoy array for the first time, we find that the intraseasonal SST variability is indeed amplified by the dSST in most of the tropical oceans, especially in the Indo‐Pacific warm pool, but weakened in the equatorial cold tongues of the Pacific and Atlantic Oceans. Such a divergent response is associated with the difference in atmosphere‐ocean interaction processes over these two regions. In the warm pool region, SST responds to the intraseasonal atmospheric variability, resulting in in‐phase intraseasonal fluctuations between SST and dSST that amplify the intraseasonal SST variability. However, in the cold tongue region, SST drives the atmospheric changes, which leads to out‐of‐phase intraseasonal fluctuations between SST and dSST and thus the inhibition of the intraseasonal SST variability.

Effects of high-frequency surface wind on the intraseasonal SST associated with the Madden-Julian oscillation

The effect of high-frequency (< 20 days) wind on the intraseasonal sea surface temperature (SST) anomaly associated with the Madden-Julian oscillation (MJO) is examined by diagnosing reanalysis and outputs from a set of oceanic general circulation model (OGCM) experiments. Warm SST anomaly (SSTA) ahead of MJO convective center induces anomalous boundary-layer convergence, favoring the eastward propagation of the MJO. To understand the key physical processes contributing to the warm SSTA, the mixed-layer heat budget equation is diagnosed. The time change of SSTA ($$\partial \left\langle T \right\rangle /\partial t$$) mostly comes from shortwave radiative heating, while latent heat flux (LHF) plays the secondary role. Due to the strong nonlinearity of LHF, the high-frequency (< 20 days) wind may affect the intraseasonal LHF variability via interacting with the background state, resulting in changes in intraseasonal SSTA. Our diagnosis shows that the upscale feedback associated with high-frequency wind variability accounts for around 23% of the intraseasonal LHF in the intraseasonal SST warming region, supporting the growth of $$\partial \left\langle T \right\rangle /\partial t$$. Sensitivity experiments are then designed using an OGCM that simulates the upper-ocean temperature well, to verify the high-frequency wind effect on the intraseasonal SST variability. Once the high-frequency component of surface winds is removed in the model integration, the amplitudes of intraseasonal LHF and $$\partial \left\langle T \right\rangle /\partial t$$ are decreased, leading to reduced SSTA. The modeling results confirm the positive role of high-frequency wind in supporting the tropical intraseasonal SST variation. The findings of this study suggest that an accurate representation of high-frequency disturbances and their interaction with other components are crucial for MJO simulation and prediction.

Seasonality in Intraseasonal Sea Surface Temperature Variability Along the Sumatra‐Java Southern Coast

AbstractThis paper evaluates the intraseasonal variability of sea surface temperature (SST) along the Sumatra‐Java southern coast using available satellite‐derived oceanic and atmospheric data combined with output from a numerical model. The result reveals that the intraseasonal variability of SST is greater during boreal summer–fall (June–October) than during boreal winter–spring (November–May). Composite analysis shows a correlation between positive/negative intraseasonal SST variabilities and coastal downwelling/upwelling, as well as onshore/offshore Ekman transport during summer–fall. During this period, with the significantly increasing role of oceanic advection, oceanic processes are evidently enhanced and dominate the intraseasonal variability of SST. Meanwhile, the contribution of atmospheric processes drops by 67%. During winter–spring, the intraseasonal SST is primarily contributed by atmospheric processes but has a nonsignificant relationship with sea level anomalies. Intraseasonal SST anomalies vary out of phase with surface wind anomalies. The result also shows a relatively small contribution by vertical processes throughout the year, with the maximum in April and the minimum during August–September. Further analysis reveals that the alternating dominance of atmospheric and oceanic processes on intraseasonal variability of SST is responsible for the seasonality along the Sumatra‐Java southern coast. Moreover, the result indicates that the seasonality in intraseasonal SST is different in the eastern Indonesian Seas, which tends to be relatively strong in boreal winter. Distinct dominance of atmospheric and oceanic processes in intraseasonal SST is the main reason for these differences in seasonal variation characteristics.

Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation

This study investigates the impact of different specification of the underlying sea surface temperature (SST) on the prediction of intraseasonal rainfall variation associated with strong Monsoon Intraseasonal Oscillation (MISO) events in the northern Indian Ocean. A series of forecast experiments forced with observed hourly, daily, or seasonal SSTs are performed for three selected strong MISO events using the National Centers for Environmental Predictions (NCEP) atmospheric Global Forecast System (GFS). The comparison between these GFS forecasts shows that the intraseasonal SST variability is more important than its diurnal variability in the MISO prediction. The GFS experiments forced with daily SST which includes intraseasonal variability has higher prediction skill and faster speed in the northward propagation of the MISO intraseasonal rainfall anomalies than those forced with seasonal SST that do not include intraseasonal variability. No significant difference is found in the MISO prediction when GFS was forced by SST with or without SST diurnal cycle. The GFS runs forced with warmer and colder seasonal SSTs which mimic possible biases in SST prediction have comparable skill in the MISO prediction. A modified version of the NCEP Climate Forecast System coupled model (CFSm5) with 1- and 10-m vertical resolutions in the upper ocean is then used to examine their performance in the MISO prediction when all aspects of SST are actively included. The CFSm5 with 1-m vertical resolution in the upper ocean (CFSm501) shows larger amplitude of intraseasonal SST anomaly, with higher prediction skill in both intraseasonal SST and rainfall than the CFSm5 with the typical 10-m vertical resolution in the upper ocean (CFSm510) does. Compared with the uncoupled GFS, both CFSm501 and CFSm510, despite errors in predicted SSTs, have better prediction skill and more reasonable rainfall variability, which is attributed to the inclusion of active air–sea interaction. These results suggest the importance of intraseasonal variability of SST and air–sea interaction in improving the intraseasonal rainfall prediction associated with the MISO.

Diagnosing Ocean Feedbacks to the BSISO: SST‐Modulated Surface Fluxes and the Moist Static Energy Budget

AbstractThe oceanic feedback to the atmospheric boreal summer intraseasonal oscillation (BSISO) is examined by diagnosing the sea surface temperature (SST) modification of surface fluxes and moist static energy on intraseasonal scales. SST variability affects intraseasonal surface latent heat (LH) and sensible heat (SH) fluxes, through its influence on air‐sea moisture and temperature gradients (∆q and ∆T, respectively). According to bulk formula decomposition, LH is mainly determined by wind‐driven flux perturbations, while SH is more sensitive to thermodynamic flux perturbations. SST fluctuations tend to increase the thermodynamic flux perturbations over active BSISO regions, but this is largely offset by the wind‐driven flux perturbations. Enhanced surface fluxes induced by intraseasonal SST anomalies are located ahead (north) of the convective center over both the Indian Ocean and the western Pacific, favoring BSISO northward propagation. Analysis of budgets of column‐integrated moist static energy (⟨m⟩) and its time rate of change (∂⟨m⟩/∂t) shows that SST‐modulated surface fluxes can influence the development and propagation of the BSISO, respectively. LH and SH variability induced by intraseasonal SSTs maintain 1–2% of ⟨m⟩ day−1 over the equatorial western Indian Ocean, Arabian Sea, and Bay of Bengal but damp about 1% of ⟨m⟩ day−1 over the western North Pacific. The contribution of intraseasonal SST variability to ∂⟨m⟩/∂t can reach 12–20% over active BSISO regions. These results suggest that SST variability is conducive, but perhaps not essential, for the propagation of convection during the BSISO life cycle.

Summer precipitation–SST relationship on different time scales in the northern tropical Indian Ocean and western Pacific

The time-lag relationship between precipitation and sea surface temperature (SST) variations depends upon the time scale. The present study compares the relationship between precipitation and SST variations on three time scales (synoptic, intraseasonal, and interannual) during boreal summer in the North Indian Ocean and the western North Pacific region. On interannual time scale, higher SST is followed by more rain rate in the Arabian Sea, but less rain rate in the Philippine Sea. On intraseasonal and synoptic time scales, higher SST precedes more rain rate. It is shown that the precipitation perturbation following the SST perturbation is more robust in the Philippine Sea on interannual and intraseasonal variations and less robust in the Arabian Sea on synoptic variations. The increase of rain rate perturbation leads to a decrease of SST on all the three time scales. The SST change in response to precipitation perturbation is more robust in the Philippine Sea and the South China Sea than in the Arabian Sea and the Bay of Bengal on interannual and intraseasonal variations. The correlation between intraseasonal precipitation and SST variations tends to be stronger when SST is above than below 29 °C in the South China Sea and the Philippine Sea. The correlation between intraseasonal precipitation perturbation and precipitation-induced SST change displays a decrease with total rain rate in the Arabian Sea and the Bay of Bengal.

Summer Intraseasonal Surface Heat Flux‐Sea Surface Temperature Relationship Over Northern Tropical Indo‐Western Pacific in Climate Models

AbstractThe present study documents the relationship between intraseasonal net surface heat flux (NHF, positive for downward flux) and sea surface temperature (SST) variations over the North Indian Ocean and tropical western North Pacific during May through September in climate models. A distinct NHF‐SST relationship is identified in the NCC.NorESM1‐M model. NHF has a weak correlation with the SST tendency but a large negative correlation with SST in the NCC.NorESM1‐M model, whereas NHF has a large positive correlation with the SST tendency and a weak correlation with SST in observations and some other climate models. The sea‐air humidity difference has a dominant contribution to latent heat flux variations in relation to a bias toward larger mean wind speed in the NCC.NorESM1‐M model. In contrast, surface wind speed overcomes the sea‐air humidity difference in contributing to latent heat flux variations due to a bias toward larger mean sea‐air humidity difference in the INM.inmcm4 model. Detailed analysis reveals different processes in intraseasonal SST variations in the South China Sea between the INM.inmcm4 and NCC.NorESM1‐M models. In the INM.inmcm4 model, atmosphere‐induced shortwave radiation and latent heat flux have a main contribution to the SST change. In the NCC.NorESM1‐M model, the SST change is mainly due to oceanic processes. The ocean‐induced positive SST anomalies increase evaporation and surface air humidity. This destabilizes the atmospheric boundary layer in favor of convection and reduced downward shortwave radiation. NHF has a damping effect on the SST change.

The 30–50-Day Intraseasonal Oscillation of SST and Precipitation in the South Tropical Indian Ocean

The Sea Surface Temperature (SST) in the South Tropical Indian Ocean (STIO) displays significant intraseasonal oscillation (ISO) in two regions. A striking 30–50-day ISO found over the east of thermocline ridge (Region A, 80–90° E, 6–12° S), as identified by the Empirical Mode Decomposition (EMD) method, is distinguished from the SST signature over the thermocline ridge (Region B, 52.5–65° E, 6–13° S). The 30–50-day ISO of SST in the Region A is active in March–May (MAM) and suppressed in September–November (SON). Meanwhile, a 30–50-day ISO of precipitation correlates with the SST over the Region A. SST leads precipitation by 10 days, implying a pronounced ocean–atmosphere interaction at the intraseasonal timescale, especially the oceanic feedback to the atmosphere during Madden–Julian Oscillation (MJO) events. Analysis on mechanism of the ISO manifests heat fluxes are critical to the development of the intraseasonal SST variability. The local thermocline in Region A, as the shallowest in MAM and the thickest in SON, is likely to modulate the strength of ISO and contribute to its sustainability. It suggests that thermocline plays a more important role in Region A than in Region B, leading to the difference between the two regions.

Bay of Bengal salinity stratification and Indian summer monsoon intraseasonal oscillation: 2. Impact on SST and convection

AbstractThe Indian summer monsoon intraseasonal oscillations (MISOs) induce pronounced intraseasonal sea surface temperature (SST) variability in the Bay of Bengal (BoB), which has important feedbacks to atmospheric convection. An ocean general circulation model (OGCM) is employed to investigate the upper‐ocean processes affecting intraseasonal SST variability and its feedback to the MISO convection. In the BoB, the MISO induces intraseasonal SST variability predominantly through surface heat flux forcing with comparable contributions from shortwave radiation and turbulent heat flux, and to a much smaller extent through wind‐driven ocean mixed layer entrainment. The ocean salinity stratification, represented by mixed layer depth (MLD) and barrier layer thickness (BLT), has a strong control on SST but weak impact on convection of the MISO. The MLD is critical for the amplitude of SST response to various forcing processes, while the BLT mainly affects entrainment by determining the temperature difference between the mixed layer and the water below. From May to mid‐June, the shallow MLD and thin barrier layer greatly enhance intraseasonal SST anomalies, which can amplify convection fluctuations of the MISO through air‐sea interaction and leads to intense but short‐duration postconvection break spells. When either the MLD or the BLT is large, intraseasonal SSTs tend to be weak. Further investigation reveals that freshwater flux of the monsoon gives rise to the shallow MLD and thick barrier layer, and its overall effect on intraseasonal SSTs is a 20% enhancement. These results provide implications for improving the simulation and forecast of the MISO in climate models.

Intraseasonal Variability of SST and Precipitation in the Arabian Sea during the Indian Summer Monsoon: Impact of Ocean Mixed Layer Depth

Abstract This study investigates sea surface temperature (SST) and precipitation variations in the eastern Arabian Sea (EAS) induced by the northward-propagating Indian summer monsoon (ISM) intraseasonal oscillations (MISOs) through analyzing satellite observations and the Climate Forecast System Reanalysis (CFSR) and performing ocean general circulation model (OGCM) experiments. MISOs in the EAS achieve the largest intensity in the developing stage (May–June) of the ISM. The MISOs induce intraseasonal SST variability primarily through surface heat flux forcing, contributed by both shortwave radiation and turbulent heat flux, and secondarily through mixed layer entrainment. The shallow mixed layer depth (MLD &amp;lt; 40 m) in the developing stage and decaying stage (September–October) of the ISM significantly amplifies the heat flux forcing effect on SST and causes large intraseasonal SST variability. Meanwhile, the high SST (&amp;gt;29°C) in the developing stage leads to enhanced response of MISO convection to SST anomaly. It means that the ocean state of the EAS region during the developing stage favors active two-way air–sea interaction and the formation of the strong first-pulse MISO event. These results provide compelling evidence for the vital role played by the ocean in the MISO mechanisms and have implications for understanding and forecasting the ISM onset. Compared to satellite observation, MISOs in CFSR data have weaker SST variability by ~50% and biased SST–precipitation relation. Reducing these biases in CFSR, which provides initial conditions of the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2), may help improve the ISM rainfall forecast.

Covariations of SST and surface heat flux on 10–20 day and 30–60 day time scales over the South China Sea and western North Pacific

AbstractThis study investigates the variability and relationship between intraseasonal sea surface temperature (SST) and surface net heat flux (NHF) variations in the South China Sea and western North Pacific regions. It is shown that the intraseasonal SST variations and their coherence with surface heat flux variations display large differences between winter and summer and between 10–20 day and 30–60 day time scales. The intraseasonal SST variability is comparable on 10–20 day and 30–60 day time scales but larger during summer than during winter. The NHF variability is much larger on the 10–20 day time scale and during winter. The coherence between intraseasonal SST and NHF variations is higher during summer than during winter due to the seasonal change in the mixed‐layer depth. During summer, coherent intraseasonal SST and NHF variations are identified in a southwest‐northeast tilted region from the South China Sea to the subtropics on the 10–20 day time scale but within a broad zonal band from the South China Sea to the Philippine Sea on the 30–60 day time scale. Such difference is not discernable during winter. The contribution of NHF to the SST tendency is larger on the 30–60 day time scale than on the 10–20 day time scale and during summer than during winter. Latent heat flux provides a much larger contribution than shortwave radiation to intraseasonal SST variations in most regions except for the South China Sea during summer on the 30–60 day time scale.

Coupled intraseasonal variations in the East Asian winter monsoon and the South China Sea–western North Pacific SST in boreal winter

The sea surface temperature (SST) in the South China Sea (SCS) displays prominent intraseasonal variations during boreal winter with a spectrum peak in the 10–30-day time period. These intraseasonal SST variations are closely associated with intraseasonal variations of the East Asian winter monsoon (EAWM). A weak EAWM is preceded by cooler SST and followed by warmer SST in the SCS and subtropical western North Pacific. A coherent southward propagation is seen in the SCS in SST, surface wind, and latent heat flux anomalies. This southward propagation is attributed to the wind-evaporation-SST effect under climatological northerly winds in winter, which differs from summer when climatological winds are westerly. The SST-induced wind speed anomalies are larger to the north side of SST anomalies. This induces larger surface evaporation anomalies to the north side, leading to a southward displacement of large SST anomalies. In turn, wind and evaporation anomalies move southward. There appears to be a positive feedback between circulation and precipitation that leads to amplification of meridional wind anomalies when the SST anomalies are weak. Surface latent heat flux is a dominant factor for the SST change in the SCS and the Yellow Sea. Shortwave radiation has a complementary contribution to the SST change in the SCS, but has a negative effect in the Yellow Sea. The wind-induced Ekman advection appears important for the SST warming in the Yellow Sea.

Intraseasonal Sea Surface Temperature Variability across the Indonesian Seas*

Abstract Sea surface temperature (SST) variability at intraseasonal time scales across the Indonesian Seas during January 1998–mid-2012 is examined. The intraseasonal variability is most energetic in the Banda and Timor Seas, with a standard deviation of 0.4°–0.5°C, representing 55%–60% of total nonseasonal SST variance. A slab ocean model demonstrates that intraseasonal air–sea heat flux variability, largely attributed to the Madden–Julian oscillation (MJO), accounts for 69%–78% intraseasonal SST variability in the Banda and Timor Seas. While the slab ocean model accurately reproduces the observed intraseasonal SST variations during the northern winter months, it underestimates the summer variability. The authors posit that this is a consequence of a more vigorous cooling effect induced by ocean processes during the summer. Two strong MJO cycles occurred in late 2007–early 2008, and their imprints were clearly evident in the SST of the Banda and Timor Seas. The passive phase of the MJO [enhanced outgoing longwave radiation (OLR) and weak zonal wind stress) projects on SST as a warming period, while the active phase (suppressed OLR and westerly wind bursts) projects on SST as a cooling phase. SST also displays significant intraseasonal variations in the Sulawesi Sea, but these differ in characteristics from those of the Banda and Timor Seas and are attributed to ocean eddies and atmospheric processes independent from the MJO.

Intraseasonal variability of upwelling in the equatorial Eastern Indian Ocean

AbstractBy analyzing satellite observations and conducting a series of ocean general circulation model experiments, this study examines the physical processes that determine intraseasonal variability (ISV) of the equatorial eastern Indian Ocean (EIO) upwelling for the 2001–2011 period. The ISV of EIO upwelling—as indicated by sea level, thermocline depth, and sea surface temperature (SST)—is predominantly forced by atmospheric intraseasonal oscillations (ISOs), and shows larger amplitudes during winter‐spring season (November–April) when atmospheric ISOs are stronger than summer‐fall (May–October). The chlorophyll (Chl‐a) concentration, another indicator of upwelling, however reveals its largest intraseasonal variability during May–October, when the mean thermocline is shallow and seasonal upwelling occurs. For both winter‐spring and summer‐fall seasons, the ISV of EIO sea level and thermocline depth is dominated by remote forcing from the equatorial Indian Ocean wind stress, which drives Kelvin waves that propagate along the equator and subsequently along the Sumatra‐Java coasts. Local wind forcing within the EIO plays a secondary role. The ISV of SST, however, is dominated by upwelling induced by remote equatorial wind only during summer‐fall, with less contribution from surface heat fluxes for this season. During winter‐spring, the ISV of SST results primarily from shortwave radiation and turbulent heat flux induced by wind speed associated with the ISOs, and local forcing dominates the SST variability. In this season, the mean thermocline is deep in the warm pool and thus thermocline variability decouples from the ISV of SST. Only in summer‐fall when the mean thermocline is shallow, upwelling has important impact on SST.

Intraseasonal variability of mixed layer depth in the tropical Indian Ocean

In this paper, we use an observational dataset built from Argo in situ profiles to describe the main large-scale patterns of intraseasonal mixed layer depth (MLD) variations in the Indian Ocean. An eddy permitting (0.25°) regional ocean model that generally agrees well with those observed estimates is then used to investigate the mechanisms that drive MLD intraseasonal variations and to assess their potential impact on the related SST response. During summer, intraseasonal MLD variations in the Bay of Bengal and eastern equatorial Indian Ocean primarily respond to active/break convective phases of the summer monsoon. In the southern Arabian Sea, summer MLD variations are largely driven by seemingly-independent intraseasonal fluctuations of the Findlater jet intensity. During winter, the Madden–Julian Oscillation drives most of the intraseasonal MLD variability in the eastern equatorial Indian Ocean. Large winter MLD signals in northern Arabian Sea can, on the other hand, be related to advection of continental temperature anomalies from the northern end of the basin. In all the aforementioned regions, peak-to-peak MLD variations usually reach 10 m, but can exceed 20 m for the largest events. Buoyancy flux and wind stirring contribute to intraseasonal MLD fluctuations in roughly equal proportions, except for the Northern Arabian Sea in winter, where buoyancy fluxes dominate. A simple slab ocean analysis finally suggests that the impact of these MLD fluctuations on intraseasonal sea surface temperature variability is probably rather weak, because of the compensating effects of thermal capacity and sunlight penetration: a thin mixed-layer is more efficiently warmed at the surface by heat fluxes but loses more solar flux through its lower base.

Intraseasonal SST variations in the South China Sea during boreal winter and impacts of the East Asian winter monsoon

AbstractPresent study documents the intraseasonal variability of sea surface temperature (SST) in the South China Sea (SCS) during boreal winter and its association with the East Asian winter monsoon (EAWM) variability. In northern Tropics, the largest intraseasonal variability of SST during boreal winter is found in the SCS, with two localized regions of large standard deviation, one extending westward from the Luzon Strait and the other extending southward from the coast of central Vietnam. Correspondingly, large intraseasonal variability in surface heat fluxes is observed in the above regions. Analysis shows that the formation of large intraseasonal SST anomalies in these regions is attributed largely to wind‐related surface latent heat flux changes, with supplementary contribution from cloud‐related surface shortwave radiation changes. Wind‐induced Ekman advection has a negative effect, and the Ekman upwelling pattern differs from the intraseasonal SST anomaly pattern. The intraseasonal variations of SST in the SCS display a close association with the East Asian winter monsoon (EAWM) change with a time lag of 3–5 days. In a weak (strong) phase of the EAWM, decrease (increase) in surface wind speed and suppression (enhancement) in surface latent heat flux lead to intraseasonal SST warming (cooling). This intraseasonal SST signal displays a southward propagation with the SST change in northern SCS leading that in southern SCS by about 2 days. A similar southward propagation is seen in surface wind speed and latent heat flux anomalies. The southward propagation of cloud and shortwave radiation anomalies is limited to northern part of the SCS.

Contrast of local air–sea relationships between 10–20-day and 30–60-day intraseasonal oscillations during May–September over the South China Sea and western North Pacific

Present study compares local air–sea relationship of 10–20-day and 30–60-day intraseasonal oscillations (ISOs) over the South China Sea (SCS) and western North Pacific (WNP) during May through September for the period 1998–2010. It is shown that sea surface temperature (SST) has a larger intraseasonal variance in the North Indian Ocean, the SCS, and subtropical WNP on the 30–60-day time scale, but in tropical WNP on the 10–20-day time scale. The local correlation of SST with rain, surface shortwave radiation (SWR) and latent heat flux (LHF) displays a southwest–northeast tilted structure on the 10–20-day time scale, but a broad west-east pattern with a larger correlation on the 30–60-day time scale. The time of SST leading rain is larger in off-equatorial regions than in near-equatorial regions for both types of ISOs, whereas the time of rain leading SST is larger in near-equatorial regions than in off-equatorial regions. A similar feature is seen for SWR, but an opposite feature for LHF. The atmospheric ISOs induce intraseasonal SST variations through cloud-radiation and wind-evaporation changes. The intraseasonal SST variations feedback on the atmosphere through modulation of atmospheric stability over off-equatorial regions on both timescales. The SST impacts on the atmosphere appear larger on the 30–60-day time scale than on the 10–20-day time scale. The distinct spatial patterns of local air–sea relationship on the two types of ISOs are associated with different spatial structures in both atmospheric ISO-associated SWR and LHF anomalies and SST-induced atmospheric stability anomalies.