Energetics of lower tropospheric ultra-long waves: A key to intra-seasonal variability of Indian monsoon
S M Bawiskar, M D Chipade and P V Puranik
Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pune 411 008, India.
e-mail: bawiskar@hotmail.com

Abstract: Analysis of fifty four (1951 –2004)years of daily energetics of zonal waves derived from NCEP/ NCAR wind (u and v data and daily rainfall received over the Indian landmass (real time data) during southwest monsoon season (1 June –30 September)indicate that energetics (momentum transport and kinetic energy)of lower tropospheric ultra-long waves (waves 1 and 2)of low latitudes hold a key to intra-seasonal variability of monsoon rainfall over India. Correlation coe fficient between climatology of daily (122 days)energetics of ultra-long waves and climatology of daily rainfall over Indian landmass is 0.9.The relation is not only signi ficant but also has a predictive potential.The normalised plot of both the series clearly indicates that the response period of rainfall to the energetics is of 5 –10 days during the onset phase and 4 –7 days during the withdrawal phase of monsoon over India.During the established phase of monsoon, both the series move hand-in-hand.Normalised plot of energetics of ultra-long waves and rainfall for individual year do not show marked deviation with respect to climatology.These results are first of its kind and are useful for the short range forecast of rainfall over India.



Summer monsoon onset over Kerala:New definition and prediction
D S Pai*  and Rajeevan M Nair
National Climate Centre, Pune 411 005, Maharashtra, India.
∗e-mail: sivapai@hotmail.com

Abstract: The summer monsoon onset over Kerala (MOK)marks the beginning of the rainy season for the country.Associated with the MOK,signi ficant transitions of large scale atmospheric and oceanic circulation patterns are observed over the Asia –Paci fic region.In this study,a new method for the objective identi fication of MOK,based on large scale circulation features and rainfall over Kerala,is discussed.Further,a set of empirical models based on the principal component regression (PCR)technique was developed for the prediction of the date of MOK by keeping in mind the IMD ’s operational forecasting service requirements.Predictors for the models were derived using correlation analysis from the thermal,convective and circulation patterns.Only five predictors pertaining to the second half of April were used in the first model (Model-1)so that the prediction of MOK can be prepared by the end of April itself.The second model (Model-2)used four additional predictors pertaining up to the first half of May along with two predictors used in the Model-1 for update prediction at the end of the first half of May.To develop each of the PCR models, Principal Components Analysis (PCA)of the respective predictor data was carried out followed by regression analysis of first two principal components (PCs)with the date of MOK.Both these models showed good skill in predicting the date of MOK during the independent test period of 1997 –2007.The root mean square error (RMSE)of the predictions from both the models during the independent test period was about four days which was nearly half the RMSE of the predictions based on climatology.


Distribution of particulate carbohydrate species
in the Bay of Bengal
Vishwas B Khodse*,Narayan B Bhosle and V V Gopalkrishna
Council of Scientific and Industrial Research, Marine Corrosion and Material Research Division,
National Institute of Oceanography, Dona Paula 403 004, Goa, India.
∗e-mail: vkhodse@nio.org

Abstract: Suspended particulate matter (SPM)of surface seawaters was collected during December 2003 to October 2004 at 10 stations in the Bay of Bengal,and analyzed for particulate organic carbon (POC),total particulate nitrogen (TPN),total particulate carbohydrate (TPCHO)and total par- ticulate uronic acids (TPURA).The concentrations of POC,TPCHO and TPURA varied from 4.80 to 29.12,0.85 to 4.24,0.09 to 0.91 µ C,respectively.The TPCHO-C and TPURA-C accounted for 6.6 –32.5%and 0.87 –3.65%of POC.The trends observed for the distribution of these compounds were generally similar to those recorded for the distribution of chlorophyll a (Chl a .The C/N ratios varied from 3.2 to 22.3 with most of the values being < 10.This suggests that the organic matter was mostly derived from phytoplankton and bacteria.Relatively low C/N ratios and high TPCHO yield imply that freshly derived organic matter was present during SWM and FIM.Our data suggest that the quality and quantity of organic matter varied spatially and seasonally.


Coral microatoll as geodetic tool in North Andaman
and Little Andaman, India
S K Som*,Vijay Shivgotra and Ashim Saha
Earthquake Geology Division,Geological Survey of India,Eastern Region,DK-Block,
Sector-II,Salt Lake City,Kolkata 700 091,India.
∗email:sksom@redi ffmail.com

Abstract: Coral microatolls were examined from North Andaman and Little Andaman to understand the relative sea level change due to vertical tectonic deformation above the subduction interface.The highest level of survival of coral microatoll before the 26 December,2004 earthquake at eastern coast of North Andaman has been determined by Global Ocean Tide Model.The present position of recently dead flat top microatoll with preserved internal structure at the eastern coast of North Andaman mainland indicates 31.21 cm uplift due to the 26 December,2004 earthquake.Compara- tively old cup shaped microatoll at the eastern fringe of North Andaman group of islands and highly bioeroded fossil microatolls at the intertidal zone of Little Andaman bear the signature of permanent vertical deformation in the past.


Some observations from radiometric ‘8 bit’ data of sediment thin sections based on alternative petrographic image analysis method
Sudip Dey 1, ∗, Suvendu Ghosh 1 , Chandrani Debbarma 1 , Prasamita Sarkar 1 ,
Mhu Aris Marfai 2,3, ∗∗and Sabyasachi Maiti 4, †
1 Department of Geography and Disaster Management,Tripura University,
Suryamaninagar 799 130,Tripura,India.
2 Institute of Geography,Justus-Liebig-University,35390 Giessen,Germany
3 Geography Faculty,Gadjah Mada University,55281 Yogyakarta,Indonesia.
4 Department of Geology and Geophysics,Indian Institute of Technology,Kharagpur,India.
∗e-mail:sudip −geo@redi ffmail.com
∗∗e-mail:Muh.Marfai@geogr.uni-giessen.de
†e-mail:maiti@gg.iitkgp.ernet.in

Abstract: This paper deals with the experiment of sediment microstructure analysis especially microfabric mapping by digital imaging.For that purpose the greyscale images (Red band from RGB com- bination)of the thin sections have been prepared from the selected 12 samples.The basis of this mapping is the re flectance capacity of di fferent sediments which is in fluenced by the physi- cal parameters like grain size and colour.The re flectances of di fferent sediments are represented in digital format by di fferent DN values from 0 –255 within the radiometric ranges of ‘8 bit ’data. Density slicing has been chosen as the method of microstructure mapping in this research.This study shows that lower DN values normally present dark coloured coarser sand and clay while higher DN values present light coloured finer sediment samples.In the selected samples for this study the maximum DN value has been found from micaceous materials.Another remarkable thing observed from the microfabric mapping is that the presence of coarser sediments forms complex microfabric pattern than the finer sediments in the study area.Though this method have some demerits,still its simple technique can be very useful for accurate microstructure analysis.


Linear genetic programming for time-series modelling of daily flow rate
Aytac Guven
Civil Engineering Department, Gaziantep University, 27310 Gaziantep, Turkey.
e-mail: aguven@gantep.edu.tr

Abstract: In this study linear genetic programming (LGP),which is a variant of Genetic Programming,and two versions of Neural Networks (NNs)are used in predicting time-series of daily flow rates at a station on Schuylkill River at Berne,PA,USA.Daily flow rate at present is being predicted based on di fferent time-series scenarios.For this purpose,various LGP and NN models are calibrated with training sets and validated by testing sets.Additionally,the robustness of the proposed LGP and NN models are evaluated by application data,which are used neither in training nor at testing stage.The results showed that both techniques predicted the flow rate data in quite good agreement with the observed ones,and the predictions of LGP and NN are challenging.The performance of LGP,which was moderately better than NN,is very promising and hence supports the use of LGP in predicting of river flow data.


Comments on ‘Volatile displacement of Meghalaya coals –A pointer to explore low sulphur coals’ by P Behera (J. Earth Syst. Sci., 116, April 2007, 137–142)
Rabindra Nath Hota
P.G. Department of Geology, Utkal University, Vani Vihar, Bhubaneswar 751 004, India.


Reply to the comments by Rabindra Nath Hota on ‘Volatile displacement of Meghalaya coals – A pointer to explore low sulphur coals’
P Behera
P.G. Department of Geology, Utkal University, Vani Vihar, Bhubaneswar 751 004, India.
e-mail: pn −behera@indiatimes.com