Numerical Simulations of the Impacts of Land-Cover Change on Cold Fronts in South-West Western Australia

The south-west of Western Australia has experienced significant land-cover change as well as a decline in rainfall. Given that most precipitation in the region results from frontal passages, the impact of land-cover change on the dynamics of cold fronts is explored using the Regional Atmospheric Modeling System version 6.0. Frontal simulations are evaluated against high resolution atmospheric soundings, station observations, and gridded rainfall analyses and shown to reproduce the qualitative features of cold fronts. Land-cover change results in a decrease in total frontal precipitation through a decrease in boundary-layer turbulent kinetic energy and vertically integrated moisture convergence, and an increase in wind speed within the lower boundary layer. Such processes contribute to reduced convective rainfall under current vegetation cover.     

Seasonal variation of microzooplankton (20–200 μm) and its possible implications on the vertical carbon flux in the western Bay of Bengal

Stratification (throughout the year) and low solar radiation (during monsoon periods) have caused low chlorophyll a and primary production (seasonal average 13–18 mg m⁻² and 242–265 mg C m⁻² d⁻¹, respectively) in the western Bay of Bengal (BoB). The microzooplankton (MZP) community of BoB was numerically dominated by heterotrophic dinoflagellates (HDS) followed by ciliates (CTS). The highest MZP abundance (average 665±226×10⁴ m⁻²), biomass (average 260±145 mg C m⁻²) and species diversity (Shannon weaver index 2.8±0.42 for CTS and 2.6±0.35 for HDS) have occurred during the spring intermonsoon (SIM). This might be due to high abundance of smaller phytoplankton in the western BoB during SIM as a consequence of intense stratification and nitrate limitation (nitracline at 60 m depth). The strong stratification during SIM was biologically evidenced by intense blooms of Trichodesmium erythraeum and frequent Synechococcus–HDS associations. The high abundance of smaller phytoplankton favors microbial food webs where photosynthetic carbon is channeled to higher trophic levels through MZP. This causes less efficient transfer of primary organic carbon to higher trophic levels than through the traditional food web. The microbial food web dominant in the western BoB during SIM might be responsible for the lowest mesozooplankton biomass observed (average 223 mg C m⁻²). The long residence time of the organic carbon in the surface waters due to the active herbivorous pathways of the microbial food web could be a causative factor for the low vertical flux of biogenic carbon during SIM.     

Monthly prediction of rainfall over India and its homogeneous zones during monsoon season: a supervised principal component regression approach on general circulation model products

A supervised principal component regression (SPCR) technique has been employed on general circulation model (GCM) products for developing a monthly scale deterministic forecast of summer monsoon rainfall (June–July–August–September) for different homogeneous zones and India as a whole. The time series of the monthly observed rainfall as the predictand variable has been used from India Meteorological Department gridded (1°?×?1°) rainfall data. Lead 0 (forecast initialized in the same month) monthly products from GCMs are used as predictors. The sources of these GCMs are International Research Institute for Climate and Society, Columbia University, National Center for Environmental Prediction, and Japan Agency for Marine Earth Science and Technology. The performance of SPCR technique is judged against simple ensemble mean of GCMs (EM) and it is found that over almost all the zones the SPCR model gives better skill than EM in June, August, and September months of monsoon. The SPCR technique is able to capture the year to year observed rainfall variability in terms of sign as well as the magnitude. The independent forecasts of 2007 and 2008 are also analyzed for different monsoon months (Jun–Sep) in homogeneous zones and country. Here, 1982–2006 have been considered as development year or training period. Results of the study suggest that the SPCR model is able to catch the observational rainfall over India as a whole in June, August, and September in 2007 and June, July, and August in 2008.     

IMPLICIT NONLINEAR NORMAL MODE INITIALIZATION:A MULTIGRID APPROACH

The implicit nonlinear normal mode initialization (INMI) is applied to a tropical limited area shallow water modelin spherical coordinates.The boundary condition for the INMI scheme is based on the boundary formulation of themodel.The INMI scheme is found to be very efficient in suppressing spurious gravity wave oscillation and providing awell balanced initial data set for the model.The INMI scheme involves solving a number of elliptic type equations withvarying complexity.and hence an efficient numerical technique is required for solving such equations.In order to makeINMI computationally more attractive,we are employing the multigrid method for solving all the elliptic type equationsin the INMI scheme.The numerical procedures for the development of such multigrid solvers are briefly described.     

Study of terrestrial carbon flux by eddy covariance method in revegetated manganese mine spoil dump at Gumgaon,India

The micrometeorological technique of eddy covariance is a powerful tool for characterizing the carbon (C) budget of terrestrial ecosystems. Eddy covariance method was used for estimating Net Ecosystem Exchange (NEE) of carbon dioxide between atmosphere and revegetated manganese mine spoil dump at Gumgaon, India. In this paper, we analyzed the diel CO₂ flux pattern and its response to various physical environmental conditions. The carbon balance of terrestrial ecosystems is particularly sensitive to climatic changes. Study of diel pattern of CO₂ flux showed that carbon uptake was dependent on sunlight. Effect of temperature and latent heat on the CO₂ flux showed that rate of CO₂ uptake increased proportionally, but later declined due to various factors like stomatal response, high evaporative demand, circadian rhythm and/or a combination of all three. Net ecosystem production of revegetated land was found to be 28.196 KgC/ha/day whereas average net carbon release by the ecosystem, through respiration was observed to be 5.433 KgC/ha/day. Thus, quantifying net carbon (C) storage in degraded land is a necessary step in the validation of carbon sequestration estimates and in assessing the possible role of these ecosystems in offsetting adverse impacts of fossil fuel emissions.     

Construction of vertical wind profile from satellite-derived winds for objective analysis of wind field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pres-sure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations The pur-pose of these additional systems was to make the best possible data for the studies on various aspects of monsoon cir-culation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further infer-red that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.     

Performance of image classification on hyperspectral imagery for lithological mapping

SVM and SAM classifiers for the lithological mapping using Hyperion data in parts of Gadag schist belt of western Dharwar craton, Karnataka, India were used. The main objective of the present study is to assess and compare the potential use of Hyperion data set for lithological mapping. Accuracy assessment of the derived thematic maps was based on the analysis of the confusion matrix statistics computed for each classification map. For consistency, the same set of validation points were used in evaluating the accuracy of the lithological thematic maps produced. On the basis of the accuracy assessment results, it appears that SVM generally outperformed the SAM classifier in both OA accuracy and individual classes’ accuracies. OA accuracy and Kc for SVM is 96.93% and 0.9655, whereas for SAM it is 74.02% and 0.7085 respectively. SVM classification is the best in describing the spatial distribution and the cover density of each lithology, as was also indicated from the statistics of the individual class results. The individual class accuracy were also analyzed for the SVM and the result show that PA ranges from 87% to 100% and UA ranges from 91% to 100%, whereas for SAM ranges from 15% to 95%, and from 31% to 100% respectively. The SVM method could effectively classify and improve on the existing geological map for the Gadag schist belt (GSB) using hyperspectral data. The results could be validated through field visits. Therefore, it is concluded that hyperspectral remote sensing data can be efficiently used to improve existing maps, especially in areas where same rock types show variable degree of alteration over smaller spatial scales.