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_aArun Varriar P P (92213008) _98316 |
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| 245 | _aEvaluation of dynamical downscaled daily precipitation and temperature indices over India in present-day climate | ||
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_bMaster of Science in Computational Science _c2013-2015 _dEXT _eT.K Manoj Kumar _fJ. Sanjay (Scientist-E) _g"Centre for Climate Change Research (CCCR), Indian Institute of Tropical Meteorology (IITM), Pune" |
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| 520 | _aThe main aim of this project is to understand the basic concepts of climate extremes and mastering how to analyse them using the statistical tool R. This study provide a first look at the performance of high resolution dynamical downscaling of a global reanalyses data set using a regional climate model (RCM) in simulating climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over India under the present-day climate. First, the ETCCDI indices based on weather station observations and reanalysis available globally at a coarse resolution are intercompared with few selected indices computed by the same ETCCDI methodology using the high resolution gridded observations available over India. The high resolution climate extreme indices calculated in this study are found to be more reliable for better understanding the sub-regional spatial variations over India at annual and seasonal time scales, than the coarser resolution ETCDDI indices. These observed high resolution climate extreme indices are used to assess the value added to reanalysis with dynamical downscaling by evaluating the performance of the RCM simulated daily precipitation and temperature indices over India under the present‐day climate. The detailed evaluation of their climatologically monthly seasonal cycle and interannual variations over two sub-regions over India highlighted the strengths and weaknesses of the downscaled RCM simulation. | ||
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_aINFORMATION SYSTEMS _98317 |
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_aINFORMATION SYSTEMS APPLICATIONS _98318 |
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_aR _98319 |
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_2ddc _cPR |
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_c4939 _d4939 |
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