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[1] Regional climate models are becoming increasingly popular to provide high resolution climate change information for impacts assessments to inform adaptation options. Many countries and provinces requiring these assessments are as small as 200,000 km 2 in size, significantly smaller than an ideal domain needed for successful applications of one-way nested regional climate models. Therefore assessments on sub-regional scales (e.g., river basins) are generally carried out using climate change simulations performed for relatively larger regions. Here we show that the seasonal mean hydrological cycle and the day-to-day precipitation variations of a sub-region within the model domain are sensitive to the domain size, even though the large scale circulation features over the region are largely insensitive. On seasonal timescales, the relatively smaller domains intensify the hydrological cycle by increasing the net transport of moisture into the study region and thereby enhancing the precipitation and local recycling of moisture. On daily timescales, the simulations run over smaller domains produce higher number of moderate precipitation days in the sub-region relative to the corresponding larger domain simulations. An assessment of daily variations of water vapor and the vertical velocity within the sub-region indicates that the smaller domains may favor more frequent moderate uplifting and subsequent precipitation in the region. The results remained largely insensitive to the horizontal resolution of the model, indicating the robustness of the domain size influence on the regional model solutions. These domain size dependent precipitation characteristics have the potential to add one more level of uncertainty to the downscaled projections.Citation: Bhaskaran, B., A. Ramachandran, R. Jones, and W. Moufouma-Okia (2012), Regional climate model applications on sub-regional scales over the Indian monsoon region: The role of domain size on downscaling uncertainty,

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The study was aimed at assessing the effects of indigenous Plant Growth Promoting Bacterium (PGPB) on the legume Pongamia pinnata in the degraded soil of the Nanmangalam Reserve Forest (NRF) under nursery conditions. In total, 160 diazotrophs were isolated from three different nitrogen-free semi-solid media (LGI, Nfb, and JMV). Amongst these isolates, Pseudomonas aeruginosa RRALC3 exhibited the maximum ammonia production and hence was selected for further studies. RRALC3 was found to possess multiple plant growth promoting traits such as nitrogen accumulation (120.6ppm); it yielded a positive amplicon with nifH specific primers, tested positive for Indole Acetic Acid (IAA; 18.3μg/ml) and siderophore production, tested negative for HCN production and was observed to promote solubilization of phosphate, silicate and zinc in the plate assay. The 16S rDNA sequence of RRALC3 exhibited 99% sequence similarity to Pseudomonas aeruginosa JCM5962. Absence of virulence genes and non-hemolytic activity indicated that RRALC3 is unlikely to be a human pathogen. When the effects of RRALC3 on promotion of plant growth was tested in Pongamia pinnata, it was observed that in Pongamia seedlings treated with a combination of RRALC3 and chemical fertilizer, the dry matter increased by 30.75%. Nitrogen, phosphorus and potassium uptake increased by 34.1%, 27.08%, and 31.84%, respectively, when compared to control. Significant enhancement of total sugar, amino acids and organic acids content, by 23.4%, 29.39%, and 26.53% respectively, was seen in the root exudates of P. pinnata. The carbon content appreciated by 4-fold, when fertilized seedlings were treated with RRALC3. From the logistic equation, the rapid C accumulation time of Pongamia was computed as 43 days longer than the control when a combination of native PGPB and inorganic fertilizer was applied. The rapid accumulation time of N, P and K in Pongamia when treated with the same combination as above was 15, 40 and 33 days longer, respectively, as compared to the control.

BackgroundUrban malaria is considered to be one of the most significant infectious diseases due to varied socioeconomic problems especially in tropical countries like India. Among the south Indian cities, Chennai is endemic for malaria. The present study aimed to identify the hot spots of malaria prevalence and the relationship with other factors in Chennai during 2005-2011.MethodsData on zone-wise and ward-wise monthly malaria positive cases were collected from the Vector Control Office, Chennai Corporation, for the year 2005 to 2011 and verified using field data. This data was used to calculate the prevalence among thousand people. Hotspot analysis for all the years in the study period was done to observe the spatial trend. Association of environmental factors like altitude, population density and climatic variables was assessed using ArcGIS 9.3 version and SPSS 11.5. Pearson’s correlation of climate parameters at 95% and 99% was considered to be the most significant. Social parameters of the highly malaria prone region were evaluated through a structured random questionnaire field survey.ResultsAmong the ten zones of Chennai Corporation, Basin Bridge zone showed high malaria prevalence during the study period. The ‘hotspot’ analysis of malaria prevalence showed the emergence of newer hotspots in the Adyar zone. These hotspots of high prevalence are places of moderately populated and moderately elevated areas. The prevalence of malaria in Chennai could be due to rainfall and temperature, as there is a significant correlation with monthly rainfall and one month lag of monthly mean temperature. Further it has been observed that the socioeconomic status of people in the malaria hotspot regions and unhygienic living conditions were likely to aggravate the malaria problem.ConclusionMalaria hotspots will be the best method to use for targeting malaria control activities. Proper awareness and periodical monitoring of malaria is one of the quintessential steps to control this infectious disease. It has been argued that identifying the key environmental conditions favourable for the occurrence and spread of malaria must be integrated and documented to aid future predictions of malaria in Chennai.