THE northward-propagating intraseasonal oscillations

Similar documents
Impacts of intraseasonal oscillation on the onset and interannual variation of the Indian summer monsoon

RECTIFICATION OF THE MADDEN-JULIAN OSCILLATION INTO THE ENSO CYCLE

MODELING INDIAN OCEAN CIRCULATION: BAY OF BENGAL FRESH PLUME AND ARABIAN SEA MINI WARM POOL

Variance-Preserving Power Spectral Analysis of Current, Wind and 20º Isothermal Depth of RAMA Project from the Equatorial Indian Ocean

Causes of the Intraseasonal SST Variability in the Tropical Indian Ocean

Analysis of 2012 Indian Ocean Dipole Behavior

Monsoon IntraSeasonal Oscillation (MISO) in the Bay of Bengal: Effect of mixed layer and barrier layer on SST and convection

Satellite observations of intense intraseasonal cooling events in the tropical south Indian Ocean

Investigation of Common Mode of Variability in Boreal Summer Intraseasonal Oscillation and Tropospheric Biennial Oscillation

Interannual variation of northeast monsoon rainfall over southern peninsular India

Lecture 33. Indian Ocean Dipole: part 2

The OCEANS and Indian Monsoon. Climate Variability

Comparison of the Structure and Evolution of Intraseasonal Oscillations Before and After Onset of the Asian Summer Monsoon

Long period waves in the coastal regions of north Indian Ocean

Influence of El Nino Southern Oscillation and Indian Ocean Dipole in biennial oscillation of Indian summer monsoon

Wintertime intraseasonal SST variability in the tropical South Indian Ocean and Role of Ocean Dynamics in the MJO Initiation

UNIFIED MECHANISM OF ENSO CONTROL ON INDIAN MONSOON RAINFALL SUNEET DWIVEDI

Influence of enhanced convection over Southeast Asia on blocking ridge and associated surface high over Siberia in winter

Mechanistic links between the tropical Atlantic and the Indian monsoon in the absence of El Nino Southern Oscillation events

Intraseasonal Surface Fluxes in the Tropical Western Pacific and Indian Oceans from NCEP Reanalyses

ENSO and monsoon induced sea level changes and their impacts along the Indian coastline

Indian Ocean warming its extent, and impact on the monsoon and marine productivity

3 The monsoon currents in an OGCM

Ocean Mixed Layer Temperature Variations Induced by Intraseasonal Convective Perturbations over the Indian Ocean

Increasing intensity of El Niño in the central equatorial Pacific

Biennial Oscillation of Tropical Ocean-Atmosphere System Associated with Indian Summer Monsoon

Variability in the tropical oceans - Monitoring and prediction of El Niño and La Niña -

The MJO-Kelvin wave transition

Systematic Validation of Conductivity and Temperature from Ocean moored buoy data in the northern Indian Ocean with in situ ship based measurements

Understanding El Nino-Monsoon teleconnections

Evaluation of ACME coupled simulation Jack Reeves Eyre, Michael Brunke, and Xubin Zeng (PI) University of Arizona 4/19/3017

332 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 6, NO. 2, APRIL X/$ IEEE

Mesoscale air-sea interaction and feedback in the western Arabian Sea

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, C04001, doi: /2006jc003791, 2007

Local vs. Remote SST Forcing in Shaping the Asian-Australian Monsoon Variability

The Air-Sea Interaction. Masanori Konda Kyoto University

Decadal changes in the relationship between Indian and Australian summer monsoons

LONG- TERM CHANGE IN PRE- MONSOON THERMAL INDEX OVER CENTRAL INDIAN REGION AND SOUTH WEST MONSOON VARIABILITY

Periodic Forcing and ENSO Suppression in the Cane- Zebiak Model

Long-term warming trend over the Indian Ocean

Decadal amplitude modulation of two types of ENSO and its relationship with the mean state

Northward propagation of the subseasonal variability over the eastern Pacific warm pool

Validation of SST and Windspeed from TRMM using North Indian Ocean Moored Buoy Observations

Hui Wang, Mike Young, and Liming Zhou School of Earth and Atmospheric Sciences Georgia Institute of Technology Atlanta, Georgia

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 4 September 2012

The slab ocean El Niño

An ITCZ-like convergence zone over the Indian Ocean in boreal late autumn

Lecture 13 El Niño/La Niña Ocean-Atmosphere Interaction. Idealized 3-Cell Model of Wind Patterns on a Rotating Earth. Previous Lecture!

10.6 The Dynamics of Drainage Flows Developed on a Low Angle Slope in a Large Valley Sharon Zhong 1 and C. David Whiteman 2

Intraseasonal Variability in Sea Level Height in the Bay of Bengal: Remote vs. local wind forcing & Comparison with the NE Pacific Warm Pool

CHAPTER 6 DISCUSSION ON WAVE PREDICTION METHODS

ASSESSMENT OF SEA BREEZE CHARACTERISTICS FROM SODAR ECHOGRAMS

Intra-seasonal Vagaries of the Indian Summer Monsoon Rainfall

Super-parameterization of boundary layer roll vortices in tropical cyclone models

The Amplitude-Duration Relation of Observed El Niño Events

On some aspects of Indian Ocean Warm Pool

Role of Mid-Latitude Westerly Trough Index at 500 h Pa and its Association with Rainfall in Summer Monsoon over Indian Region

Lecture 20. Active-weak spells and breaks in the monsoon: Part 1

Climatology of the 10-m wind along the west coast of South American from 30 years of high-resolution reanalysis

Use of Interactions between NAO and MJO for the Prediction of Dry and Wet Spell in Monsoon Season

Traditional El Niño and El Niño Modoki Revisited: Is El Niño Modoki Linearly Independent of Traditional El Niño?

Basin-wide warming of the Indian Ocean during El Niño and Indian Ocean dipole years

The Great Paradox of Indian Monsoon Failure (Unraveling The Mystery of Indian Monsoon Failure During El Niño)

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 8 March 2010

Ocean dynamic processes responsible for the interannual. variability of the tropical Indian Ocean SST. associated with ENSO

The Role of the Wind-Evaporation-Sea Surface Temperature (WES) Feedback in Tropical Climate Variability

Data Analysis of the Seasonal Variation of the Java Upwelling System and Its Representation in CMIP5 Models

SST 1. ITCZ ITCZ. (Hastenrath and Heller 1977; Folland et al. 1986; Nobre and Shukla 1996; Xie and Carton 2004). 2. MIROC. (Namias 1972).

Onset of Indian summer monsoon over Gadanki (13.5 N, 79.2 E): Study using lower atmospheric wind profiler

The warm pool in the Indian Ocean

The impacts of explicitly simulated gravity waves on large-scale circulation in the

EL NIÑO AND ITS IMPACT ON CORAL REEF ECOSYSTEM IN THE EASTERN INDIAN OCEAN

Effect of sea surface temperature on monsoon rainfall in a coastal region of India

Wind-Driven Response of the Northern Indian Ocean to Climate Extremes*

Influence of mechanical mixing on a low summertime SST in the western North Pacific ITCZ region

Indian Ocean Seasonal Cycle Jérôme Vialard (IRD) LOCEAN Paris France From Schott & McCreary (Prog. Oc.

Impact of Atmospheric Intraseasonal Oscillations on the Indian Ocean Dipole during the 1990s*

Andrew Turner Publication list. Submitted

Influence of atmospheric intraseasonal oscillations on seasonal and interannual variability in the upper Indian Ocean

Increasing trend of break-monsoon conditions over India - Role of ocean-atmosphere processes in the Indian Ocean

Subsurface Ocean Indices for Central-Pacific and Eastern-Pacific Types of ENSO

Subsurface Ocean Temperature Indices for Central-Pacific and Eastern-Pacific Types of El Niño and La Niña Events

Factors controlling January April rainfall over southern India and Sri Lanka

How fast will be the phase-transition of 15/16 El Nino?

Atmospheric Forcing and the Structure and Evolution of the Upper Ocean in the Bay of Bengal

Chapter 2. Turbulence and the Planetary Boundary Layer

Sea surface salinity variability during the Indian Ocean Dipole and ENSO events in the tropical Indian Ocean

ENSO IMPACT ON SST AND SLA VARIABILITY IN INDONESIA

Variability of intraseasonal Kelvin waves in the equatorial Pacific Ocean

PROC. ITB Eng. Science Vol. 36 B, No. 2, 2004,

Asymmetry in zonal phase propagation of ENSO sea surface temperature anomalies

Impact of Typhoons on the Western Pacific: Temporal and horizontal variability of SST cooling Annual Report, 2011 James F. Price

An ocean-atmosphere index for ENSO and its relation to Indian monsoon rainfall

Haibo Hu Jie He Qigang Wu Yuan Zhang

Interannual Variability of the Upper Ocean in the Southeast Pacific Stratus Cloud Region

Effect of Orography on Land and Ocean Surface Temperature

Indian Ocean Dipole - ENSO - monsoon connections and Overcoming coupled model systematic errors

Second peak in the far eastern Pacific sea surface temperature anomaly following strong El Niño events

Goal: Develop quantitative understanding of ENSO genesis, evolution, and impacts

Subsurface equatorial zonal current in the eastern Indian Ocean

Transcription:

206 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 2, MARCH 2011 Diurnal Cycle Induced Amplification of Sea Surface Temperature Intraseasonal Oscillations Over the Bay of Bengal in Summer Monsoon Season Milind Mujumdar, Kiran Salunke, Suryachandra A. Rao, M. Ravichandran, and B. N. Goswami Abstract In spite of strong mean summer monsoon winds, the magnitudes of diurnal and intraseasonal oscillations (ISO) of the sea surface temperature (SST) in the Bay of Bengal (BoB) are as strong as the respective magnitudes in the western Pacific. Using continuous observations during the peak summer monsoon of 1998 at BoB buoy (DS4) located at (89 E, 19 N), we show that the strong near-surface diurnal variation in the BoB during warming phases of the ISO leads to almost double the magnitude of the diurnal SST over the BoB as compared to that during the cooling phases. The simulation experiments with and without the diurnal cycle of surface fluxes indicate that more than one-third of the observed SST ISO amplitude could arise from the rectification of the diurnal cycle through the influence of late night and early daytime upper-ocean mixing processes during the warming phases. The rapid shoaling of the upper-ocean mixed layer occurs during afternoon while it deepens slowly during late night and early daytime which tends to retain the warm SSTs at the end of the nighttime cooling. The insight derived from these experiments on the influence of the diurnal cycle on ISOs of the SST underlines the need for a proper simulation of the diurnal cycle of the SST in climate models. Index Terms Amplification, diurnal cycle, intraseasonal variability, sea surface temperature. I. INTRODUCTION THE northward-propagating intraseasonal oscillations (ISOs) with associated active and break spells constitute a major building block for the south Asian summer monsoon [8]. With an amplitude as large as the annual cycle, the ISOs represent a large signal and contribute significantly to the seasonal mean and its interannual variability. They also cluster the synoptic variability and control probability of the occurrence of heavy rain events [9]. The monsoon ISOs have shown to arise from the coupling between the atmosphere and the ocean [7], [11], [14] and known to be associated with large amplitude sea surface temperature (SST) fluctuations over the Bay of Bengal (BoB) [15]. While the enhancement of intraseasonal variability by the diurnal cycle (rectification) has been documented elsewhere [3], [4], [6], [10], [16], [17], [19], [20], it has not been demonstrated over the north Indian Manuscript received March 4, 2010; revised May 28, 2010; accepted July 11, 2010. This was supported by the Indian National Centre for Ocean Information Services under sponsored project Variations in the Warm Pool and its Association With Indian Summer Monsoon. M. Mujumdar, K. Salunke, S. A. Rao, and B. N. Goswami are with the Indian Institute of Tropical Meteorology, Pune 411 008, India. M. Ravichandran is with the Indian National Centre for Ocean Information Services, Hyderabad 500 055, India. Digital Object Identifier 10.1109/LGRS.2010.2060183 Ocean or BoB, particularly during a summer monsoon. This is partly because some studies [2] indicate that the diurnal SST amplitude over the north Indian Ocean is weak, owing to systematically strong monsoon winds from May to August. However, using in situ measurements over a moored buoy location over the BoB, we demonstrate that the amplitude of the diurnal cycle of the SST over the BoB could be as large as that of the ISO. Furthermore, using a model, we show that the diurnal cycle has a significant influence in maintaining the observed amplitude of the ISO. An interesting aspect of the BoB is that it receives a large fresh water influx from intense local rain as well as from river runoff during the peak Indian summer monsoon (ISM). The large fresh water influx induces near-surface stratification in the BoB through the formation of a low-salinity layer and the increase of a vertical salinity gradient [13]. The resulting nearsurface stratification prevents the subsurface water to interact with the surface and to influence the SST and thus plays a crucial role in maintaining warmer (above 28 C) SSTs over the BoB. This makes the BoB rather unique among the tropical oceans where large amplitude ISOs thrive [11], [14], [15]. The thin low-density upper-ocean layer also makes the BoB amenable to the large diurnal variability [5]. Thus, the BoB becomes an ideal place to study the interactions between the diurnal cycle and the ISOs and their influence over each other. The structure of this letter is as follows. The next section describes the data set and methodology used for analyzing the characteristics of the diurnal cycle of the intraseasonal SST variability and for carrying out the supportive simulation experiments, followed by a section which presents the diagnosis of the diurnal characteristics of the intraseasonal variability evolving from air sea interactions. It also describes the simulations of warming and cooling phases of the SST with and without diurnal forcings. The last section provides a summary and a future scope for modeling the influence of the diurnal cycle in modulating the intraseasonal SST variability using various models. II. DATA AND METHODOLOGY Under the National Data Buoy Program (NDBP), long records of meteorological and oceanographic observations are made available over various locations of the north Indian Ocean. Out of three buoys deployed in the BoB, the buoy (DS4) located at 89 E and 19 N has continuous records of observations and depicted the strong ISO of the SST during the summer monsoon of 1998 [1], [14], [15]. It is to be noted that 1545-598X/$26.00 2010 IEEE

MUJUMDAR et al.: DIURNAL CYCLE INDUCED AMPLIFICATION OF SST ISOs OVER THE BAY OF BENGAL 207 the analysis of various warming and cooling phases of the SST over the BoB using a sporadic buoy data set (e.g., summer monsoon 2003 phases over DS3 buoy location (90 E and 12 N), figure not shown) during 1998 2003 (NDBP) exhibits consistency in the diurnal characteristics with the warming and cooling phases of the 1998 summer monsoon. It is worth mentioning here that the diagnostic and simulation analysis in this letter is focused on the peak of the 1998 ISM, June 15 September 15, which also excludes the influence of the strong seasonal cycle during onset and withdrawal phases. The three-hourly surface fluxes are calculated using three-hourly near-surface oceanographic and meteorological buoy (DS4) data sets following [1], [14], and [15]. Similarly, three-hourly outgoing long-wave radiation from Langley (http://eosweb.larc.nasa.gov) was used in calculating the net radiative fluxes. The National Center for Environmental Prediction humidity parameter (averaged over the DS4 location) is used, with a 3-h interpolation, for computing the surface heat fluxes. The amplitudes of the intraseasonal variability and diurnal cycle are calculated here following [3] and [4]. For example, the magnitude of the intraseasonal warming phases [14], [15] of the SST is calculated using a 3-day running mean of the magnitude of the diurnal cycle. Moreover, on a particular day, the difference between the daily maximum and the mean of the preceding and succeeding nocturnal minima is the amplitude of the diurnal cycle. The mean of the upper ends of the magnitude distribution for a 3-day running mean (diurnal cycle), obtained during the warming phases, is used to quantify the intraseasonal (diurnal) variability. The mixed layer depth (MLD) is calculated in this letter following [18]. The high-frequency coupling between the ocean and the atmosphere in the BoB and its possible impact on the intraseasonal time scale can be better investigated through model simulation experiments. The north and central BoB observes relatively weak surface currents and small meridional temperature gradients during the peak of the ISM, and the vertical processes have important implications in maintaining the surface temperature over the BoB region, when compared with that of the neighboring basins [3], [5], [14]. Therefore, seasonal simulation experiments with a 1-D vertical mixing model [12] at the DS4 buoy location are useful to understand the ocean atmosphere coupling processes. The subsurface climatology (Levitus climatology, http://www.nodc.noaa.gov/) is used for the model initialization while the diurnal cycle of the observed surface fluxes of heat, freshwater, and momentum determines the evolution of (ocean atmosphere feedback) the upper ocean mixing through the SST over the BoB. The control experiment (CTL) is used for validation against the observed SST and the key features of the mixed layer evolution. Similarly, the daily mean of the surface fluxes is computed and used here for carrying out the daily simulation experiment (DLY). Furthermore, a direct comparison of the CTL and DLY experiments is useful in understanding the interactions between the diurnal cycle and the intraseasonal SST variability over the BoB. III. RESULTS The warming and cooling phases in the SST at the DS4 buoy location during the peak of the 1998 ISM were identified as an ISO by Sengupta et al. [14] and Sengupta and Ravichandran [15]. Fig. 1(a) shows the daily time series of the mean SST (solid line) and the amplitude of the diurnal cycle of the SST (dashed line) during the study period. The two warming phases (during the second and third weeks of July and August with a mean magnitude of 0.83 C) and two cooling phases (during late June to early July and late July to early August with a mean magnitude of 0.51 C) are observed. In addition, during the warming phase, the diurnal amplitude is found to be generally higher (0.71 C) than that of the cooling phase (0.35 C) with as large as a 1 C peak amplitude of the diurnal cycle around August 18, 1998 [see Fig. 1(a)]. A lead of approximately 3 days in the peak of the diurnal SST and that of the daily mean SST, particularly during the warming phases is noteworthy. Furthermore, the magnitude of the low-frequency variability (see Table I) of the BoB buoy SST (0.83 C) is comparable with that of the diurnal cycle (0.71 C) as found in the west Pacific warm pool [4] [magnitudes of low frequency (0.86 C) and diurnal cycle (1.01 C)]. In a recent study, Bellenger and Duvel [2] suggested a summer time weakening of the diurnal SST amplitude over the BoB relative to the intraseasonal variability; however, this letter contradicts this. This is the first time that the distinction of the intraseasonal and diurnal amplitudes of the BoB SST during a summer monsoon season is brought out with a focus on the warming phases in particular. The 1-D model used in this letter reasonably captures day-today variations in the SST both in the CTL (thin line) and DLY (thick dashed line) runs [see Fig. 1(b)]. The simulated diurnal amplitude is distinctly different in the warming (0.68 C) and cooling (0.42 C) phases of the SST in the CTL run [see Fig. 1(b)] as in the observations (thick line). The differences in the simulated SST between the CTL and DLY runs (thin dashed line) are below 0.2 C during the cooling phases while it exceeds 0.5 C in the warming phases. The SST variability during the warming phases over the BoB region (see Table I) in the CTL run (0.76 C) is comparable with the observations while the absence of the diurnal cycle of fluxes in the DLY run results in a 35% underestimate of the intraseasonal SST variability over the BoB. Furthermore, the simulated MLD [see Fig. 1(c)] variations are coherent with the cooling (deepening) and warming (shoaling) phases of the SST [see Fig. 1(b)]. The magnitude of the diurnal variability of the MLD (thin line) is also distinctly different in the warming (5 10 m) and cooling (2 3 m) phases of the SST in the CTL run. The weaker diurnal variability of the SST during the deepening of the MLD could be attributed to the exchange of properties with the deeper ocean by entrainment at the base of the MLD. The difference of the shoaling of the MLD in the CTL and DLY runs (thin dashed line) during the warming phase exceeds 15 m. It is worth noticing that, during the warming phases, the daily net surface heat flux (Qnet, thick line) exceeds 500 W/m 2 [see Fig. 1(d)], the diurnal range (dashed line) is positive (exceeding 50 W/m 2 ), the winds are calm [see Fig. 1(e) and (f)], and the magnitude of the short wave radiation exceeds 600 W/m 2.In addition, the magnitude of the diurnal variations of the net heat flux and the winds reduces (increases) by half (twice) while, for the short wave flux, the magnitude increases (reduces) twice (half) during the warming (cooling) phases. The composites of the diurnal cycle of parameters describing the upper oceanic processes during the warm phases of the SST are shown in Fig. 2. The composite diurnal cycle of the MLD

208 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 2, MARCH 2011 Fig. 1. (a) Time series of SST for BoB Buoy (DS4) located at 89 E and 19 N during peak ISM of 1998. Thin solid line represents daily mean SST and thin dashed line represents daily range of diurnal cycle (maxima minimum). Ordinate at the left-hand side indicates magnitude of daily mean SST (degree Celsius) while the right-hand side represents amplitude of SST diurnal cycle (degree Celsius). (b) SST (degree Celsius) time series of (thick solid line) buoy observations, (thin solid line) CTL, and (thick dashed line) DLY runs during peak ISM of 1998. Time series of daily SST difference simulated by DLY and CTL runs during peak ISM of 1998 is shown by thin dashed line. (c) Same as Fig. 1(b) except for upper-ocean MLD (in meters). (d) Same as Fig. 1(a) except for net surface heat flux Qnet (Watt per square meter). (e) Same as Fig. 1(a) except for Tx. (f) Same as Fig. 1(a) except for Ty. (g) Same as Fig. 1(a) except for short wave radiative fluxes (Watt per square meter). TABLE I SUMMARY OF THE DIAGNOSTICS OF DIURNAL AND LOW-FREQUENCY VARIABILITIES DURING WARMING PHASE [black line in Fig. 2(a)] depicts a rapid shoaling in the afternoon and a gradual deepening during nighttime, which continues to deepen until the early morning. Thus, the average MLD during noon to evening time is much shallower than that during nighttime. Because of the diurnal variation of the MLD, the absorption of heat in the near-surface layer is enhanced during afternoon time, and the heat loss is lower during nighttime due to the reduction in the surface heat flux [see Fig. 2(b)]. The entrainment heat flux at the base of the mixed layer is computed following [17] and shown in Fig. 2(c). The entrainment cooling is larger during daytime than in nighttime. In particular, the entrainment cooling is largest when the mixed layer is rapidly shoaling during afternoon time. While the shoaling rate of the mixed layer is higher during afternoon [see Fig. 2(a)], the large temperature gradient at the base of the mixed layer results in the large entrainment heat flux. The entrainment cooling during late night and early morning is lower than that during afternoon and evening time. This results in enhanced warming and reduced cooling in the mixed layer prior to the strong entrainment, as shown in Fig. 2(b). From the observations (figure not shown) and the CTL (black line) run, it may be noted that the magnitude of the daytime warming of the SST is more rapid than that of the nighttime cooling [see Fig. 2(d)]. The SST, simulated by the CTL run, is relatively warmer at the end of the nighttime cooling than before the beginning of the dawn, which results in the net warming of the SST in the composite diurnal cycle. On the other hand, the DLY

MUJUMDAR et al.: DIURNAL CYCLE INDUCED AMPLIFICATION OF SST ISOs OVER THE BAY OF BENGAL 209 Fig. 2. (a) Composite diurnal cycles of (solid line) MLD and (dashed line) surface heat flux simulated by CTL run. Horizontal axis indicates local time starting from 06:00 h Indian Standard Time. (b) Same as (a) except for (solid line) surface heat flux and (dashed line) surface heat flux divided by the MLD. Both time series are normalized by the respective standard deviations. (c) Same as (a) except for the entrainment heat flux at the base of mixed layer. (d) Same as (a) except for the SST from the model experiment forced with (solid line) diurnal surface fluxes and (dashed line) daily mean surface fluxes. run depicts that the warming of the SST is lower [see Fig. 2(d)] which ultimately leads to underestimate the net warming. It may be noted that the large diurnal cycle occurs mostly during the period when the net surface heat flux is positive (warming). Moreover, it is worth mentioning that a lead of approximately 3 days in the peak of the diurnal SST and of the daily mean SST also supports the retention of the relatively warmer SST at the end of the day through the upper-ocean mixing and entrainment heat flux at the base of the mixed layer during the warming phases. These results indicate that, unlike the west Pacific [17], the SST change during the nighttime cooling period is not the same as that during the daytime warming period [see Fig. 2(d)] over the BoB. This could be due to the strong stratification resulting from a river inflow and intense precipitation. The spectrum analysis of the daily buoy SST during the peak ISM of 1998 is carried out, and power spectra of the representative time series are shown in Fig. 3(a). The spectral peaks with its statistical significance illustrate the existence of a significant power in the different frequency ranges. A strong power with a 99% significance level at the 10-day range is well separated from that of a higher frequency at subsynoptic to synoptic scales. However, the power at the 30 60-day range has a 90% confidence level and is beyond the scope of this letter. The spectrum analysis of the daily SST [see Fig. 3(b)], simulated by the CTL run during the peak ISM of 1998, exhibits close agreement with the aforementioned diagnosis [see Fig. 3(a)]. The SST simulated by the CTL run has two spectral peaks at the 10-day range and at the synoptic range. It is worth noticing that the previously mentioned analysis is carried out on the SST data sets, which explicitly resolve the diurnal cycle. It is therefore interesting to carry out the spectrum analysis on the SST [see Fig. 3(c)] simulated by the DLY run in which the diurnal cycle is excluded. The spectral peak around the 10-day range is barely significant at the 90% level. Moreover, both the spectral peaks seen at the 99% confidence level in Fig. 3(a) and (b) are missing in Fig. 3(c). This suggests the significant interaction between the diurnal and ISO modes mediated through the synoptic variability. Thus, the DLY run depicts the underestimation of the intraseasonal variability of the daily mean SST, clearly indicating that the rectification of the intraseasonal variability can occur through the diurnal cycle. IV. SUMMARY AND FUTURE SCOPE The influence of the diurnal cycle on the intraseasonal SST variability over the BoB region is investigated using the DS4 buoy data and 1-D mixed layer model experiments with (CTL run) and without (DLY run) diurnal forcings. The comparable magnitudes of the intraseasonal variability of the BoB buoy SST and that of the diurnal cycle are found to be similar to those of the west Pacific SST variability. The simulation experiments with and without the diurnal cycle of the surface fluxes indicate that more than one-third of the observed SST ISO amplitude could arise from the rectification of the diurnal cycle. The simulation experiments with and without the diurnal forcings depict the overall agreement in capturing the warming and cooling phases of the SST. However, the upper-ocean mixing process responsible for the rectification of the intraseasonal

210 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 2, MARCH 2011 ACKNOWLEDGMENT The authors would like to thank the two anonymous reviewers for their critical comments and suggestions, which helped to significantly improve the quality and clarity of this letter. M. Mujumdar would like to thank the support of Jaison, Ghrage, Hemant, Samir, Anant, Sahai, and Krishnan. Fig. 3. Variance spectra of BoB daily SST during peak ISM of 1998 for (a) observations, (b) CTL run, and (c) DLY run. Spectral power is indicated on y-axis, and period (in days) is shown on x-axis. Upper, middle, and lower curves represent the significance level of 99%, 95% and 90%, respectively. SST variability could be simulated in the CTL run only. In particular, during the warming phases, the rapid shoaling of the upper-ocean mixed layer during afternoon and evening time and the relatively slow deepening during late night and early daytime depict the strong near-surface diurnal variation in the BoB appropriately. The comparison of the simulation experiments with and without the diurnal cycle forcings reveals that most of the diurnal and intraseasonal characteristics of the SST variability are influenced by the slowly varying nature of the surface fluxes. The composites of the diurnal cycle of the parameters, during the warming phases of the SST, describing the upperoceanic processes explain the enhancement of absorption of heat in the near surface during afternoon time. The analysis of the entrainment heat flux at the base of the mixed layer during the warming phases suggests that the enhanced warming during afternoon and the reduced nighttime cooling in the mixed layer retains the relatively warmer SST at the end of the day. This analysis also indicates that the magnitude of the daytime warming is not the same as that of the nighttime cooling. The spectrum analysis of the observed and simulated SST data sets reveals the possibility of interaction between the diurnal and ISO modes mediated through intermediate variability. Thus, the incorporation of the diurnal forcing is crucial while simulating the diurnal and intraseasonal SST variability. It is worth carrying this study further using in situ 2-D data and oceanic general circulation model to quantify the role of the diurnal cycle in the SST in the modulation of the ISO signal over the BoB. Hence, a well-designed network of observations is very much essential for the appropriate representation of scale interactions. REFERENCES [1] N. Agarwal, R. Sharma, S. Basu, A. Parekh, A. Sarkar, and V. K. Agarwal, Bay of Bengal summer monsoon 10 day variability in sea surface temperature using model and observations, Geophys. Res. Lett., vol. 34, p. L06 602, 2007. DOI:10.1029/2007GL029296. [2] H. Bellenger and J.-P. Duvel, An analysis of tropical ocean diurnal warm layers, J. Clim., vol. 22, no. 13, pp. 3629 3646, Jul. 2009. [3] D. J. Bernie, E. Guilyardi, G. Madec, J. M. Slingo, and S. J. Woolnough, Impact of resolving the diurnal cycle in an ocean atmosphere GCM. Part 1: A diurnally forced OGCM, Clim. Dyn., vol. 29, no. 6, pp. 575 590, Nov. 2007. [4] D. J. Bernie, S. J. Woolnough, J. M. Slingo, and E. Guilyardi, Modelling diurnal and intraseasonal variability of the ocean mixed layer, J. Clim., vol. 18, no. 8, pp. 1190 1202, Apr. 2005. [5] G. S. Bhat, S. Gadgil, P. V. Hareesh Kumar, S. R. Kalsi, P. Madhusoodanan, V. S. N. Murty, C. V. K. Prasada Rao, V. Ramesh Babu, L. V. G. Rao, R. R. Rao, M. Ravichandran, K. G. Reddy, P. Sanjeeva Rao, D. Sengupta, D. R. Sikka, J. Swain, and P. N. Vinayachandran, BOBMEX: The Bay of Bengal monsoon experiment, Bull. Amer. Meteorol. Soc., vol. 82, pp. 2217 2243, 2001. [6] C. de Boyer, C. Montegut, J. Vialard, S. S. C. Shenoi, D. Shankar, F. Durand, C. Ethé, and G. Madec, Simulated seasonal and interannual variability of mixed layer heat budget in the Northern Indian Ocean, J. Clim., vol. 20, no. 13, pp. 3249 3268, Jul. 2007. [7] X. Fu, B. Wang, T. Li, and J. P. McCreary, Coupling between northwardpropagating, intraseasonal oscillations and sea surface temperature in the Indian Ocean, J. Atmos. Sci., vol. 60, no. 15, pp. 1733 1753, Aug. 2003. [8] B. N. Goswami, G. Wu, and T. Yasunari, Annual cycle, intraseasonal oscillations and roadblock to seasonal predictability of the Asian summer monsoon, J. Clim., vol. 19, no. 20, pp. 5078 5099, Oct. 2006. [9] B. N. Goswami, R. S. Ajaya Mohan, P. K. Xavier, and D. Sengupta, Clustering of low pressure systems during the indian summer monsoon by intraseasonal oscillations, Geophys. Res. Lett., vol. 30, no. 8, p. 1431, 2003. DOI: 10.1029/2002GL016734. [10] H. H. Hendon, Impact of air sea coupling on the Madden Julian oscillation in a general circulation model, J. Atmos. Sci., vol. 57, no. 24, pp. 3939 3952, Dec. 2000. [11] T. N. Krishnamurti, D. K. Oosterhof, and A. V. Mehta, Air sea interaction on the time scale of 30 to 50 days, J. Atmos. Sci., vol. 45, no. 8, pp. 1304 1322, Apr. 1988. [12] J. F. Price, R. A. Weller, and R. R. Schudlich, Wind-driven ocean currents and Ekman transport, Science, vol. 238, no. 4833, pp. 1534 1538, Dec. 1987. [13] S. A. Rao, V. V. Gopalkrishna, S. R. Shetye, and T. Yamagata, Why were cool SST anomalies in the Bay of Bengal during the 1997 Indian Ocean Dipole Event? Geophys. Res. Lett., vol. 29, pp. 50 54, 2002. [14] D. Sengupta, B. N. Goswami, and R. Senan, Coherent intraseasonal oscillations of ocean and atmosphere during the Asian summer monsoon, Geophys. Res. Lett., vol. 28, no. 21, pp. 4127 4130, Nov. 2001. [15] D. Sengupta and M. Ravichandran, Oscillations of Bay of Bengal sea surface temperature during 1998 summer monsoon, Geophys. Res. Lett., vol. 28, no. 10, pp. 2033 2036, May 2001. [16] T. Shinoda and H. H. Hendon, Intraseasonal variability of surface fluxes and sea surface temperature in the tropical western Pacific and Indian Ocean, J. Clim., vol. 11, no. 7, pp. 1685 1702, Jul. 1998. [17] T. Shinoda, Impact of the diurnal cycle of solar radiation on intraseasonal SST variability in the western equatorial Pacific, J. Clim.,vol.18,no.14, pp. 2628 2636, Jul. 2005. [18] J. Vialard and P. Delecluse, An OGCM study for the TOGA decade. Part I: Role of salinity in the physics of the western equatorial fresh pool, J. Phys. Oceanogr., vol. 28, pp. 1071 1088, 1998. [19] D. E. Waliser, K. M. Lau, and J. H. Kim, The influence of coupled sea surface temperatures on the Madden Julian oscillation: A model perturbation experiment, J. Atmos. Sci., vol. 56, no. 3, pp. 333 358, Feb. 1999. [20] B. Wang and X. Xie, Coupled modes of the warm pool climate system. Part I: The role of air sea interaction in maintaining Madden Julian oscillation, J. Clim., vol. 11, no. 8, pp. 2116 2135, Aug. 1998.