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.

Spatial Variability of the Depth of Weathered and Engineering Bedrock using Multichannel Analysis of Surface Wave Method

In this paper an attempt has been made to evaluate the spatial variability of the depth of weathered and engineering bedrock in Bangalore, south India using Multichannel Analysis of Surface Wave (MASW) survey. One-dimensional MASW survey has been carried out at 58 locations and shear-wave velocities are measured. Using velocity profiles, the depth of weathered rock and engineering rock surface levels has been determined. Based on the literature, shear-wave velocity of 330 ± 30 m/s for weathered rock or soft rock and 760 ± 60 m/s for engineering rock or hard rock has been considered. Depths corresponding to these velocity ranges are evaluated with respect to ground contour levels and top surface levels have been mapped with an interpolation technique using natural neighborhood. The depth of weathered rock varies from 1 m to about 21 m. In 58 testing locations, only 42 locations reached the depths which have a shear-wave velocity of more than 760 ± 60 m/s. The depth of engineering rock is evaluated from these data and it varies from 1 m to about 50 m. Further, these rock depths have been compared with a subsurface profile obtained from a two-dimensional (2-D) MASW survey at 20 locations and a few selected available bore logs from the deep geotechnical boreholes.

A comparative study of ordinary kriging and support vector machine models for the spatial variability of rock depth in Bangalore

In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.

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.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

Modelling the chemical weathering fluxes at the watershed scale in the Tropics (Mule Hole, South India): Relative contribution of the smectite/kaolinite assemblage versus primary minerals

We investigate the chemical weathering processes and fluxes in a small experimental watershed (SEW) through a modelling approach. The study site is the Mule Hole SEW developed on a gneissic basement located in the climatic gradient of the Western Ghats, South India. The model couples a lumped hydrological model simulating the water budget at the watershed scale to the WITCH model estimating the dissolution/precipitation rates of minerals using laboratory kinetic laws. Forcing functions and parameters of the simulation are defined by the field data. The coupled model is calibrated with stream and groundwater compositions through the testing of a large range of smectite solubility and abundance in the soil horizons. We found that, despite the low abundance of smectite in the dominant soil type of the watershed (4 vol.%), their net dissolution provides 75% of the export of dissolved silica, while primary silicate mineral dissolution releases only 15% of this flux. Overall, smectites (modelled as montmorillonites) are not stable under the present day climatic conditions. Furthermore, the dissolution of trace carbonates in the saprolitic horizon provides 50% of the calcium export at the watershed scale. Modelling results show the contrasted behavior of the two main soil types of the watershed: red soils (88% of the surface) are provider of calcium, while black soils (smectite-rich and characterized by a lower drainage) consumes calcium through overall carbonate precipitation. Our model results stress the key role played by minor/accessory minerals and by the thermodynamic properties of smectite minerals, and by the drainage of the weathering profiles on the weathering budget of a tropical watershed. (C) 2010 Elsevier B.V. All rights reserved.

Aperiodic Variability in the Cane-Zebiak Model: A Diagnostic Study

The finite predictability of the coupled ocean-atmosphere system is determined by its aperiodic variability. To gain insight regarding the predictability of such a system, a series of diagnostic studies has been carried out to investigate the role of convergence feedback in producing the aperiodic behavior of the standard version of the Cane-Zebiak model. In this model, an increase in sea surface temperature (SST) increases atmospheric heating by enhancing local evaporation (SST anomaly feedback) and low-level convergence (convergence feedback). The convergence feedback is a nonlinear function of the background mean convergence field. For the set of standard parameters used in the model, it is shown that the convergence feedback contributes importantly to the aperiodic behaviour of the model. As the strength of the convergence feedback is increased from zero to its standard value, the model variability goes from a periodic regime to an aperiodic regime through a broadening of the frequency spectrum around the basic periodicity of about 4 years. Examination of the forcing associated with the convergence feedback reveals that it is intermittent, with relatively large amplitude only during 2 or 3 months in the early part of the calendar year. This seasonality in the efficiency of the convergence feedback is related to the strong seasonality of the mean convergence over the eastern Pacific. It is shown that if the mean convergence field is fixed at its March value, aperiodic behavior is produced even in the absence of annual cycles in the other mean fields. On the, other hand, if the mean convergence field is fixed at its September value, the coupled model evolution remains close to periodic, even in the presence of the annual cycle in the other fields. The role of convergence feedback on the aperiodic variability of the model for other parameter regimes is also examined. It is shown that a range exists in the strength of the SST anomaly feedback for which the model variability is aperiodic even without the convergence feedback. It appears that in the absence of convergence feedback, enhancement of the strength of the air-sea coupling in the model through other physical processes also results in aperiodicity in the model.

Diurnal variation of atmospheric CO2 concentration and delta C-13 in an urban atmosphere during winter-role of the Nocturnal Boundary Layer

The paper presents the importance of the Nocturnal Boundary Layer in driving the diurnal variability of the atmospheric CO2 mixing ratio and the carbon isotope ratio at ground level from an urban station in India. Our observations are the first of their kind from this region. The atmospheric CO2 mixing ratio and the carbon isotopic ratio were measured for both the morning (05:30-07:30 IST) and afternoon time (16:00-18:00 IST) air samples at 5 m above ground level in Bangalore city, Karnataka State (12 degrees 58' N, 77 degrees 38' E, masl = 920 m) for a 10 day period during the winter of 2008. We observed a change of similar to 7% the in CO2 mixing ratio between the morning and afternoon time air samples. A stable isotope analysis of CO2 from morning samples showed a depletion in the carbon isotope ratio by similar to 2 parts per thousand compared to the afternoon samples. Along with the ground-based measurement of air samples, data of radiosonde measurements were also obtained from the Indian Meteorological Department to identify the vertical atmospheric structure at different time in a day. We proposed the presence or absence of the NBL as a controlling factor for the observed variability in the mixing ratio as well as its isotopic composition. Here we used the Keeling model approach to find out the carbon isotope ratio for the local sources. The local sources have further been characterized as anthropogenic and biological respiration (in %) using a two-component mixing model. We also used a vertical mixing model based on the concept of the mixing of isotopically depleted (carbon isotope) ``polluted air'' (PA) with isotopically enriched ``free atmospheric air'' (FA) above. Using this modeling approach, the contribution of FA at ground level is being estimated for both the morning and afternoon time air samples.

Hydroclimatic influence of large-scale circulation on the variability of reservoir inflow

In this study, the nature of basin-scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large-scale circulation information from Indian Ocean is also equally important in addition to the El Nino-Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large-scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large-scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction.

Processes of 30-90 days sea surface temperature variability in the northern Indian Ocean during boreal summer

During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against similar to 0.25 for wind stress) and in observations (0.8 regression coefficient); similar to 60% of the heat flux variation is due do shortwave radiation and similar to 40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our similar to 100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

Climatic variability in Central Indian Himalaya during the last similar to 1800 years: Evidence from a high resolution speleothem record

Stable isotopes from a U/Th dated aragonite stalagmite from the Central Kumaun Himalaya provide evidence of variation in climatic conditions in the last similar to 1800 years. The delta O-18 and delta C-13 values vary from -4.3 parts per thousand to -7.6 parts per thousand and -3.4 parts per thousand to -9.1 parts per thousand respectively, although the stalagmite was not grown in isotopic equilibrium with cave drip water, a clear palaeoclimatic signal in stalagmite delta O-18 values is evident based on the regional climate data. The stalagmite showed a rapid growth rate during 830-910 AD, most likely the lower part of Medieval Warm Period (MWP), and 1600-1640 AD, the middle part of Little Ice Age (LIA). Two distinct phases of reduced precipitation are marked by a 2 parts per thousand shift in 8180 values towards the end of MWP (similar to 1080-1160 AD) and after its termination from similar to 1210 to 1440 AD. The LIA (similar to 1440-1880 AD) is represented by sub-tropical climate similar to modern conditions, whereas the post-LIA was comparatively drier. The Inter Tropical Convergence Zone (ITCZ) was located over the cave location during wetter/warmer conditions. When it shifted southward, precipitation over the study area decreased. A prominent drop in delta O-18 and delta C-13 values during the post-LIA period may also have been additionally influenced by anthropogenic activity in the area. (C) 2013 Elsevier Ltd and INQUA. All rights reserved.

Role of the cloud adjustment time scale in simulation of the interannual variability of Indian summer monsoon

The simulation of precipitation in a general circulation model relying on relaxed mass flux cumulus parameterization scheme is sensitive to cloud adjustment time scale (CATS). In this study, the frequency of the dominant intra-seasonal mode and interannual variability of Indian summer monsoon rainfall (ISMR) simulated by an atmospheric general circulation model is shown to be sensitive to the CATS. It has been shown that a longer CATS of about 5 h simulates the spatial distribution of the ISMR better. El Nio Southern Oscillation-ISMR relationship is also sensitive to CATS. The equatorial Indian Ocean rainfall and ISMR coupling is sensitive to CATS. Our study suggests that a careful choice of CATS is necessary for adequate simulation of spatial pattern as well as interannual variation of Indian summer monsoon precipitation.

The physics of ENSO-monsoon connection

The physical mechanism through which Ei-Nino and Southern Oscillation (ENSO) tends to produce deficient precipitation over Indian continent is investigated using both observations as well as a general circulation model. Both analysis of observations and atmospheric general circulation model (AGCM) study show that the planetary scale response associated with ENSO primarily influences the equatorial Indian Ocean region. Through this interaction it tends to favour the equatorial heat source, enhance precipitation over the equatorial Indian Ocean and indirectly cause a decrease in continental precipitation through induced subsidence. This situation is further complicated by the fact the regional tropospheric quasi biennial oscillation (QBO) has a bimodal structure over this region with large amplitude over the Indian continent. While the ENSO response has a quasi-four year periodicity and tends peak during beginning of the calendar year, the QBO mode tends to peak during northern summer. Thus, the QBO mode exerts a stronger influence on the interannual variability of the monsoon. The strength of the Indian monsoon in a given year depends on the combined effect of the ENSO and the QBO mode. Sines the two oscillations have disparate time scales, exact phase information of the two modes during northern summer is important in determining the Indian summer monsoon. The physical mechanism of the interannual variations of the Indian monsoon precipitation associated with ENSO presented here is similar to the physical process that cause intraseasonal 'active', 'break' oscillations of the monsoon.

The sensitivity of the northern hemisphere summer mean meridional circulation to changes in the large scale eddy forcing

A zonally averaged version of the Goddard Laboratory for Atmospheric Sciences (GLAS) climate model is used to study the sensitivity of the northern hemisphere (NH) summer mean meridional circulation to changes in the large scale eddy forcing. A standard solution is obtained by prescribing the latent heating field and climatological horizontal transports of heat and momentum by the eddies. The radiative heating and surface fluxes are calculated by model parameterizations. This standard solution is compared with the results of several sensitivity studies. When the eddy forcing is reduced to 0.5 times or increased to 1.5 times the climatological values, the strength of the Ferrel cells decrease or increase proportionally. It is also seen that such changes in the eddy forcing can influence the strength of theNH Hadley cell significantly. Possible impact of such changes in the large scale eddy forcing on the monsoon circulation via changes in the Hadley circulation is discussed. Sensitivity experiments including only one component of eddy forcing at a time show that the eddy momentum fluxes seem to be more important in maintaining the Ferrel cells than the eddy heat fluxes. In the absence of the eddy heat fluxes, the observed eddy momentum fluxes alone produce subtropical westerly jets which are weaker than those in the standard solution. On the other hand, the observed eddy heat fluxes alone produce subtropical westerly jets which are stronger than those in the standard solution.

Effect of soil variability on the bearing capacity of clay and in slope stability problems

Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (qc) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ qc data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.