%0 Journal Article %1 noauthororeditor %A Hajalalaina, Aime Richard %A Raherinirina, Angelo %A Ratiarison, Adolphe %A Libourel, Therese %D 2017 %J International Journal of Information Technology, Modeling and Computing (IJITMC) %K Climatology; Modeling; Process Reanalysis; Work-contex chain; %N 2/3/4 %P 1 to 10 %R DOI: 10.5121/ijitmc.2017.5401 %T Modeling Process Chain of Meteorological Reanalysis Precipitation Data Using Work Context %U https://aircconline.com/ijitmc/V5N4/5417ijitmc01.pdf %V 5 %X In this paper, we propose a models of process chain and knowledge-based of meteorological reanalysis datasets that help scientists, working in the field of climate and in particular of the rainfall evolution, to solve uncertainty of spatial resources (data, process) to monitor the rainfall evolution. Indeed, rainfall evolution mobilizes all research, various methods of meteorological reanalysis datasets processing are proposed. Meteorological reanalysis datasets available, at present, are voluminous and heterogeneous in terms of source, spatial and temporal resolutions.

@article{noauthororeditor, abstract = {In this paper, we propose a models of process chain and knowledge-based of meteorological reanalysis datasets that help scientists, working in the field of climate and in particular of the rainfall evolution, to solve uncertainty of spatial resources (data, process) to monitor the rainfall evolution. Indeed, rainfall evolution mobilizes all research, various methods of meteorological reanalysis datasets processing are proposed. Meteorological reanalysis datasets available, at present, are voluminous and heterogeneous in terms of source, spatial and temporal resolutions.}, added-at = {2022-09-30T13:36:58.000+0200}, author = {Hajalalaina, Aime Richard and Raherinirina, Angelo and Ratiarison, Adolphe and Libourel, Therese}, biburl = {https://www.bibsonomy.org/bibtex/2ec4930b6fb9d56b18246e74a0e56c866/alexafedrica}, doi = {DOI: 10.5121/ijitmc.2017.5401}, interhash = {dfe3fb4a2a6d15b39086da166ecbe0fb}, intrahash = {ec4930b6fb9d56b18246e74a0e56c866}, journal = {International Journal of Information Technology, Modeling and Computing (IJITMC)}, keywords = {Climatology; Modeling; Process Reanalysis; Work-contex chain;}, month = nov, number = {2/3/4}, pages = {1 to 10}, timestamp = {2022-09-30T13:36:58.000+0200}, title = {Modeling Process Chain of Meteorological Reanalysis Precipitation Data Using Work Context}, url = {https://aircconline.com/ijitmc/V5N4/5417ijitmc01.pdf}, volume = 5, year = 2017 }