Prof. R. Ananthakrishnan Seminar Series
Lecture-1 (15 Jan. 2018) |
Lecture-2 (9 Mar. 2018)
Lecture-3 (12 Apr. 2018) |
Lecture-6 (13 Jul. 2018)
The 10-20 day intraseasonal variation of the South Asian summer monsoon simulated by GFDL models in the AMIP experiment of CMIP5, June 2018, Sujata Mandke et.al.
Read MoreIsotopic analysis of rain water and transpired water on a few plants have been carried out during the monsoon season of 2016 and 2017 at IITM, Pune. The study shows that the oxygen isotopic compositions of the plant transpired water are strongly controlled by the soil water dynamics. During the active monsoon season, soil water content is increased which results in depleted isotopic values in the transpired water. On the other hand, during the break phases of monsoon, the soil water content is relatively low which leads to enriched isotopic values in plant transpired water. The study has implication in identifying the monsoon break phases using bio-meteorological parameter, that is, transpiration. To our knowledge, such kind of study, that is the identification of active/break phases using a bio-meteorological parameter was not reported before. Diagram: A schematic representation of the active and break phases during a monsoon season. During the active period, heavy rainfall helps increase the soil water content, as represented by blue shading. During this time soil evaporation is low and hence the soil water does not suffer significant changes in its isotopic values. On the other hand, during a break condition, low rainfall results in low soil water content (light blue shading) and in turn, high soil water evaporation. This causes enriched isotopic values in soil water, and in turn, the transpired water. The isotopic values of the transpired water are schematically represented by a sinusoidal variation as shown in the upper portion of the diagram. (Chakraborty S., Belekar A.R., Datye A., Sinha N., June 2018)
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A dynamic-thermodynamic reduced gravity ocean model embedded with a high-resolution vertical mixed layer model is introduced. Further the model is utilized to study the Bay of Bengal mixing and variability. The year to year variabilities of Bay of Bengal mixing and barrier layer are predominantly controlled by ENSO. Turbulent kinetic energy (TKE) and stability of water column dissociate and mitigate the variability of Bay of Bengal mixing when ENSO is a controlling factor. The study has implications for fine tuning the state of the art general circulation models and climate models in order to represent a robust spatiotemporal variability of surface mixing in the Bay of Bengal.
(Valsala V., Singh Shikha, Balasubramanian S., April 2018)
Biological modeling approach adopted by the Ocean Carbon-cycle Model Inter-comparison Project (OCMIP-II) provided amazingly simple but surprisingly accurate rendition of the annual mean carbon cycle for the global ocean. Nonetheless, OCMIP models are known to have seasonal biases which are typically attributed to their bulk parameterization of 'compensation depth'. Utilizing the criteria of surface Chl-a based attenuation of solar radiation and the minimum solar radiation required for production, we have proposed a new parameterization for a spatially and temporally varying 'compensation depth' which captures the seasonality in the production zone reasonably well. This new parameterization is shown to improve the seasonality of CO2 fluxes, surface ocean pCO2, biological export and new production in the major upwelling zones of the Indian Ocean. The seasonally varying compensation depth enriches the nutrient concentration in the upper ocean yielding more faithful biological exports which in turn leads to an accurate seasonality in the carbon cycle. Thus the new parameterization of variable compensation helps in achieving a seasonal balance in export and new production and improved the strength of both solubility and biological pumps for a better representation of carbon cycle. (Sreeush M G., Valsala V., Pentakota S., Prasad K. V. S. R. and Murtugudde, R, Biogeosciences,, April 2018)
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