Intraseasonal variability of Indian Ocean sea surface temperature during boreal winter: Madden-Julian Oscillation versus submonthly forcing and processes

[ 1] Intraseasonal variability of Indian Ocean sea surface temperature (SST) during boreal winter is investigated by analyzing available data and a suite of solutions to an ocean general circulation model for 1998 - 2004. This period covers the QuikSCAT and Tropical Rainfall Measuring Mission (TRMM) observations. Impacts of the 30 - 90 day and 10 - 30 day atmospheric intraseasonal oscillations (ISOs) are examined separately, with the former dominated by the Madden-Julian Oscillation (MJO) and the latter dominated by convectively coupled Rossby and Kelvin waves. The maximum variation of intraseasonal SST occurs at 10 degrees S - 2 degrees S in the wintertime Intertropical Convergence Zone (ITCZ), where the mixed layer is thin and intraseasonal wind speed reaches its maximum. The observed maximum warming ( cooling) averaged over ( 60 degrees E - 85 degrees E, 10 degrees S - 3 degrees S) is 1.13 degrees C ( - 0.97 degrees C) for the period of interest, with a standard deviation of 0.39 degrees C in winter. This SST change is forced predominantly by the MJO. While the MJO causes a basin-wide cooling ( warming) in the ITCZ region, submonthly ISOs cause a more complex SST structure that propagates southwestward in the western-central basin and southeastward in the eastern ocean. On both the MJO and submonthly timescales, winds are the deterministic factor for the SST variability. Short-wave radiation generally plays a secondary role, and effects of precipitation are negligible. The dominant role of winds results roughly equally from wind speed and stress forcing. Wind speed affects SST by altering turbulent heat fluxes and entrainment cooling. Wind stress affects SST via several local and remote oceanic processes.

Intraseasonal oscillation of total precipitable water over North Indian Ocean and its application in the diagnostic study of coastal rainfall

TRMM Microwave Imager (TMI) is reported to be a useful sensor to measure the atmospheric and oceanic parameters even in cloudy conditions. Vertically integrated specific humidity, Total Precipitable Water (TPW) retrieved from the water vapour absorption channel (22GHz.) along with 10m wind speed and rain rate derived from TMI is used to investigate the moisture variation over North Indian Ocean. Intraseasonal Oscillations (ISO) of TPW during the summer monsoon seasons 1998, 1999, and 2000 over North Indian Ocean is explored using wavelet analysis. The dominant waves in TPW during the monsoon periods and the differences in ISO over Arabian Sea and Bay of Bengal are investigated. The northward propagation of TPW anomaly and its coherence with the coastal rainfall is also studied. For the diagnostic study of heavy rainfall spells over the west coast, the intrusion of TPW over the North Arabian Sea is seen to be a useful tool.

Dynamics of ''internal'' interannual variability of the Indian summer monsoon in a GCM

1] The poor predictability of the Indian summer monsoon ( ISM) appears to be due to the fact that a large fraction of interannual variability (IAV) is governed by unpredictable "internal'' low frequency variations. Mechanisms responsible for the internal IAV of the monsoon have not been clearly identified. Here, an attempt has been made to gain insight regarding the origin of internal IAV of the seasonal ( June - September, JJAS) mean rainfall from "internal'' IAV of the ISM simulated by an atmospheric general circulation model (AGCM) driven by fixed annual cycle of sea surface temperature (SST). The underlying hypothesis that monsoon ISOs are responsible for internal IAV of the ISM is tested. The spatial and temporal characteristics of simulated summer intraseasonal oscillations ( ISOs) are found to be in good agreement with those observed. A long integration with the AGCM forced with observed SST, shows that ISO activity over the Asian monsoon region is not modulated by the observed SST variations. The internal IAV of ISM, therefore, appears to be decoupled from external IAV. Hence, insight gained from this study may be useful in understanding the observed internal IAV of ISM. The spatial structure of the ISOs has a significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season ( seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broad-band nature of the ISO spectrum allowing the time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relation is a manifestation of the binomial character of rainfall time series. The remaining 50% of the IAV may arise due to land-surface processes, interaction between high frequency variability and ISOs, etc.

Interannual variations of Indian summer monsoon in a GCM: External conditions versus internal feedbacks

The potential predictability of the Indian summer monsoon due to slowly varying sea surface temperature (SST) forcing is examined. Factors responsible for limiting the predictability are also investigated. Three multiyear simulations with the R30 version of the Geophysical Fluid Dynamics Laboratory's climate model are carried out for this purpose, The mean monsoon simulated by this model is realistic including the mean summer precipitation over the Indian continent. The interannual variability of the large-scale component of the monsoon such as the "monsoon shear index" and its teleconnection with Pacific SST is well simulated by the model in a 15-yr integration with observed SST as boundary condition. On regional scales, the skill in simulating the interannual variability of precipitation over the Indian continent by the model is rather modest and its simultaneous correlation with eastern Pacific SST is negative but poor as observed. The poor predictability of precipitation over the Indian region in the model is related to the fact that contribution to the interannual variability over this region due to slow SST variations [El Nino-Southern Oscillation (ENSO) related] is comparable to those due to regional-scale fluctuations unrelated to ENSO SST. The physical mechanism through which ENSO SST tend to produce reduction in precipitation over the Indian continent is also elucidated. A measure of internal variability of the model summer monsoon is obtained from a 20-yr integration of the same model with fixed annual cycle SST as boundary conditions but with predicted soil moisture and snow cover. A comparison of summer monsoon indexes between this run and the observed SST run shows that the internal oscillations can account for a large fraction of the simulated monsoon variability. The regional-scale oscillations in the observed SST run seems to arise from these internal oscillations. It is discovered that most of the interannual internal variability is due to an internal quasi-biennial oscillation (QBO) of the model atmosphere. Such a QBO is also found in the author's third 18-yr simulation in which fixed annual cycle of SST as well as soil moisture and snow cover are prescribed. This shows that the model QBO is not due to land-surface-atmosphere interaction. It is proposed that the model QBO arises due to an interaction between nonlinear intraseasonal oscillations and the annual cycle. Spatial structure of the QBO and its role in limiting the predictability of the Indian summer monsoon is discussed.

Multi-scale interactions and predictability of the Indian summer monsoon

Following the seminal work of Charney and Shukla (198 1), the tropical climate is recognised to be more predictable than extra tropical climate as it is largely forced by 'external' slowly varying forcing and less sensitive to initial conditions. However, the Indian summer monsoon is an exception within the tropics where 'internal' low frequency (LF) oscillations seem to make significant contribution to its interannual variability (IAV) and makes it sensitive to initial conditions. Quantitative estimate of contribution of 'internal' dynamics to IAV of Indian monsoon is made using long experiments with an atmospheric general circulation model (AGCM) and through analysis of long daily observations. Both AGCM experiments and observations indicate that more than 50% of IAV of the monsoon is contributed by 'internal' dynamics making the predictable signal (external component) burried in unpredictable noise (internal component) of comparable amplitude. Better understanding of the nature of the 'internal' LF variability is crucial for any improvement in predicition of seasonal mean monsoon. Nature of 'internal' LF variability of the monsoon and mechanism responsible for it are investigated and shown that vigorous monsoon intraseasonal oscillations (ISO's) with time scale between 10-70 days are primarily responsible for generating the 'internal' IAV. The monsoon ISO's do this through scale interactions with synoptic disturbances (1-7 day time scale) on one hand and the annual cycle on the other. The spatial structure of the monsoon ISO's is similar to that of the seasonal mean. It is shown that frequency of occurance of strong (weak) phases of the ISO is different in different seasons giving rise to stronger (weaker) than normal monsoon. Change in the large scale circulation during strong (weak) phases of the ISO make it favourable (inhibiting) for cyclogenesis and gives rise to space time clustering of synoptic activity. This process leads to enhanced (reduced) rainfall in seasons of higher frequency of occurence strong (weak) phases of monsoon ISO.

Large scale features and assessment of spatial scale correspondence between TMPA and IMD rainfall datasets over Indian landmass

Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.

Resonant Wave Interactions in the Presence of a Diurnally Varying Heat Source

Resonant interactions among equatorial waves in the presence of a diurnally varying heat source are studied in the context of the diabatic version of the equatorial beta-plane primitive equations for a motionless, hydrostatic, horizontally homogeneous and stably stratified background atmosphere. The heat source is assumed to be periodic in time and of small amplitude [i.e., O(epsilon)] and is prescribed to roughly represent the typical heating associated with deep convection in the tropical atmosphere. In this context, using the asymptotic method of multiple time scales, the free linear Rossby, Kelvin, mixed Rossby-gravity, and inertio-gravity waves, as well as their vertical structures, are obtained as leading-order solutions. These waves are shown to interact resonantly in a triad configuration at the O(e) approximation, and the dynamics of these interactions have been studied in the presence of the forcing. It is shown that for the planetary-scale wave resonant triads composed of two first baroclinic equatorially trapped waves and one barotropic Rossby mode, the spectrum of the thermal forcing is such that only one of the triad components is resonant with the heat source. As a result, to illustrate the role of the diurnal forcing in these interactions in a simplified fashion, two kinds of triads have been analyzed. The first one refers to triads composed of a k = 0 first baroclinic geostrophic mode, which is resonant with the stationary component of the diurnal heat source, and two dispersive modes, namely, a mixed Rossby-gravity wave and a barotropic Rossby mode. The other class corresponds to triads composed of two first baroclinic inertio-gravity waves in which the highest-frequency wave resonates with a transient harmonic of the forcing. The integration of the asymptotic reduced equations for these selected resonant triads shows that the stationary component of the diurnal heat source acts as an ""accelerator"" for the energy exchanges between the two dispersive waves through the excitation of the catalyst geostrophic mode. On the other hand, since in the second class of triads the mode that resonates with the forcing is the most energetically active member because of the energy constraints imposed by the triad dynamics, the results show that the convective forcing in this case is responsible for a longer time scale modulation in the resonant interactions, generating a period doubling in the energy exchanges. The results suggest that the diurnal variation of tropical convection might play an important role in generating low-frequency fluctuations in the atmospheric circulation through resonant nonlinear interactions.

Sobre o sinal de um downscaling dinâmico às oscilações intrassazonais de precipitação no setor norte do Nordeste do Brasil

Oscilações intrassazonais são fatores controladores da variabilidade pluviométrica interanual de áreas tropicais. O conhecimento de como os modelos numéricos reproduzem suas variabilidades é importante para entender melhor suas atuações e subsidiar operações de previsão de tempo e clima. Neste artigo investiga-se a sensibilidade de um modelo de downscaling dinâmico de precipitação na reprodução das oscilações intrassazonais observadas no setor norte do Nordeste do Brasil (SNNEB - 45ºW-37ºW e 2ºS-12ºS) no período de 1974 a 2000. Os resultados mostraram que a precipitação simulada sobre o SNNEB explicou aproximadamente 70% da variabilidade da precipitação observada no trimestre fevereiro a abril nesta região. Estatísticas de médias, desvios normalizados e percentuais neste trimestre, nessa região, em anos de contrastes climáticos nos Oceanos Pacífico e Atlântico Tropicais, também foram bem capturadas pela precipitação simulada através do downscaling. Análises espectrais com uso de ondeletas mostraram que o downscaling dinâmico tem potencial para reproduzir picos espectrais de precipitação observada no SNNEB nas escalas acima de 8 dias, e nas escalas entre 64 e 128 dias para o período de 01 de janeiro a 30 de junho.

30 years of synoptic observations from Neumayer Station with links to datasets

High temporal resolution (three hours) records of temperature, wind speed and sea level pressure recorded at Antarctic research station Neumayer (70°S, 8°W) during 1982-2011 are analysed to identify oscillations from daily to intraseasonal timescales. The diurnal cycle dominates the three-hourly time series of temperature during the Antarctic summer and is almost absent during winter. In contrast, the three-hourly time series of wind speed and sea level pressure show a weak diurnal cycle. The dominant pattern of the intraseasonal variability of these quantities, which captures the out-of-phase variation of temperature and wind speed with sea level pressure, shows enhanced variability at timescales of ~ 40 days and ~ 80 days, respectively. Correlation and composite analysis reveal that these oscillations may be related to tropical intraseasonal oscillations via large-scale eastward propagating atmospheric circulation wave-trains. The second pattern of intraseasonal variability, which captures in-phase variations of temperature, wind and sea level pressure, shows enhanced variability at timescales of ~ 35, ~ 60 and ~ 120 days. These oscillations are attributed to the Southern Annular Mode/Antarctic Oscillation (SAM/AAO) which shows enhanced variability at these timescales. We argue that intraseasonal oscillations of tropical climate and SAM/AAO are related to distinct patterns of climate variables measured at Neumayer.

Quasi-periodic, global oscillations in sea level pressure on intraseasonal timescales

The sea level pressure (SLP) variability in 30-60 day intraseasonal timescales is investigated using 25 years of reanalysis data addressing two issues. The first concerns the non-zero zonal mean component of SLP near the equator and its meridional connections, and the second concerns the fast eastward propagation (EP) speed of SLP compared to that of zonal wind. It is shown that the entire globe resonates with high amplitude wave activity during some periods which may last for few to several months, followed by lull periods of varying duration. SLP variations in the tropical belt are highly coherent from 25A degrees S to 25A degrees N, uncorrelated with variations in mid latitudes and again significantly correlated but with opposite phase around 60A degrees S and 65A degrees N. Near the equator (8A degrees S-8A degrees N), the zonal mean contributes significantly to the total variance in SLP, and after its removal, SLP shows a dominant zonal wavenumber one structure having a periodicity of 40 days and EP speeds comparable to that of zonal winds in the Indian Ocean. SLP from many of the atmospheric and coupled general circulation models show similar behaviour in the meridional direction although their propagation characteristics in the tropical belt differ widely.

Mechanisms of summer intraseasonal sea surface temperature oscillations in the Bay of Bengal

Intraseasonal variations (ISV) of sea surface temperature (SST) in the Bay of Bengal (BoB) is highest in its northwestern part. An Indian Ocean model forced by QuikSCAT winds and climatological river discharge (QR run) reproduces ISV of SST, albeit with weaker magnitude. Air-sea fluxes, in the presence of a shallow mixed layer, efficiently effect intraseasonal SST fluctuations. Warming during intraseasonal events is smaller (<1°C) for June - July period and larger (1.5° to 2°C) during September, the latter due to a thinner mixed layer. To examine the effect of salinity on ISV, the model was run by artificially increasing the salinity (NORR run) and by decreasing it (MAHA10 run). In NORR, both rainfall and river discharge were switched off and in MAHA10 the discharge by river Mahanadi was increased tenfold. The spatial pattern of ISV as well as its periodicity was similar in QR, NORR and MAHA10. The ISV was stronger in NORR and weaker in MAHA10, compared to QR. In NORR, both intraseasonal warming and cooling were higher than in QR, the former due to reduced air-sea heat loss as the mean SST was lower, and the latter due to enhanced subsurface processes resulting from weaker stratification. In MAHA10, both warming and cooling were lower than in QR, the former due to higher air-sea heat loss owing to higher mean SST, and the latter due to weak subsurface processes resulting from stronger stratification. These model experiments suggest that salinity effects are crucial in determining amplitudes of intraseasonal SST variations in the BoB.

Impact of diurnal forcing on intraseasonal sea surface temperature oscillations in the Bay of Bengal

The diurnal cycle is an important mode of sea surface temperature (SST) variability in tropical oceans, influencing air-sea interaction and climate variability. Upper ocean mixing mechanisms are significant at diurnal time scales controlling the intraseasonal variability (ISV) of SST. Sensitivity experiments using an Ocean General Circulation Model (OGCM) for the summer monsoon of the year 2007 show that incorporation of diurnal cycle in the model atmospheric forcings improves the SST simulation at both intraseasonal and shorter time scales in the Bay of Bengal (BoB). The increase in SST-ISV amplitudes with diurnal forcing is approximate to 0.05 degrees C in the southern bay while it is approximate to 0.02 degrees C in the northern bay. Increased intraseasonal warming with diurnal forcing results from the increase in mixed layer heat gain from insolation, due to shoaling of the daytime mixed layer. Amplified intraseasonal cooling is dominantly controlled by the strengthening of subsurface processes owing to the nocturnal deepening of mixed layer. In the southern bay, intraseasonal variability is mainly determined by the diurnal cycle in insolation, while in the northern bay, diurnal cycle in insolation and winds have comparable contributions. Temperature inversions (TI) develop in the northern bay in the absence of diurnal variability in wind stress. In the northern bay, SST-ISV amplification is not as large as that in the southern bay due to the weaker diurnal variability of mixed layer depth (MLD) limited by salinity stratification. Diurnal variability of model MLD is not sufficient to create large modifications in mixed layer heat budget and SST-ISV in the northern bay.

Intraseasonal response of mixed layer temperature and salinity in the Bay of Bengal to heat and freshwater flux

Buoy and satellite data show pronounced subseasonal oscillations of sea surface temperature (SST) in the summertime Bay of Bengal. The SST oscillations are forced mainly by surface heat flux associated with the active break cycle of the south Asian summer monsoon. The input of freshwater (FW) from summer rain and rivers to the bay is large, but not much is known about subseasonal salinity variability. We use 2002-2007 observations from three Argo floats with 5 day repeat cycle to study the subseasonal response of temperature and salinity to surface heat and freshwater flux in the central Bay of Bengal. About 95% of Argo profiles show a shallow halocline, with substantial variability of mixed layer salinity. Estimates of surface heat and freshwater flux are based on daily satellite data sampled along the float trajectory. We find that intraseasonal variability of mixed layer temperature is mainly a response to net surface heat flux minus penetrative radiation during the summer monsoon season. In winter and spring, however, temperature variability appears to be mainly due to lateral advection rather than local heat flux. Variability of mixed layer freshwater content is generally independent of local surface flux (precipitation minus evaporation) in all seasons. There are occasions when intense monsoon rainfall leads to local freshening, but these are rare. Large fluctuations in FW appear to be due to advection, suggesting that freshwater from rivers and rain moves in eddies or filaments.

Convergence feedback and unstable low frequency oscillations in a simple coupled ocean‐atmosphere model

The role of convergence feedback on the stability of a coupled ocean‐atmosphere system is studied using model III of Hirst (1986). It is shown that the unstable coupled mode found by Hirst is greatly modified by the convergence feedback. If the convergence feedback strength exceeds a critical value, several new unstable intraseasonal modes are also introduced. These modes have very weak dependence on the wave number. These results may explain the behaviour of some coupled models and to some extent provide a mechanism for the observed aperiodicity of the El‐Nino and Southern Oscillation (ENSO) events.