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contributor authorBoukabara, Sid A.
contributor authorZhu, Tong
contributor authorTolman, Hendrik L.
contributor authorLord, Steve
contributor authorGoodman, Steven
contributor authorAtlas, Robert
contributor authorGoldberg, Mitch
contributor authorAuligne, Thomas
contributor authorPierce, Bradley
contributor authorCucurull, Lidia
contributor authorZupanski, Milija
contributor authorZhang, Man
contributor authorMoradi, Isaac
contributor authorOtkin, Jason
contributor authorSantek, David
contributor authorHoover, Brett
contributor authorPu, Zhaoxia
contributor authorZhan, Xiwu
contributor authorHain, Christopher
contributor authorKalnay, Eugenia
contributor authorHotta, Daisuke
contributor authorNolin, Scott
contributor authorBayler, Eric
contributor authorMehra, Avichal
contributor authorCasey, Sean P. F.
contributor authorLindsey, Daniel
contributor authorGrasso, Louie
contributor authorKumar, V. Krishna
contributor authorPowell, Alfred
contributor authorXu, Jianjun
contributor authorGreenwald, Thomas
contributor authorZajic, Joe
contributor authorLi, Jun
contributor authorLi, Jinliong
contributor authorLi, Bin
contributor authorLiu, Jicheng
contributor authorFang, Li
contributor authorWang, Pei
contributor authorChen, Tse-Chun
date accessioned2017-06-09T16:45:36Z
date available2017-06-09T16:45:36Z
date copyright2016/12/01
date issued2016
identifier issn0003-0007
identifier otherams-73600.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215731
description abstractn 2011, the National Oceanic and Atmospheric Administration (NOAA) began a cooperative initiative with the academic community to help address a vexing issue that has long been known as a disconnection between the operational and research realms for weather forecasting and data assimilation. The issue is the gap, more exotically referred to as the ?valley of death,? between efforts within the broader research community and NOAA?s activities, which are heavily driven by operational constraints. With the stated goals of leveraging research community efforts to benefit NOAA?s mission and offering a path to operations for the latest research activities that support the NOAA mission, satellite data assimilation in particular, this initiative aims to enhance the linkage between NOAA?s operational systems and the research efforts. A critical component is the establishment of an efficient operations-to-research (O2R) environment on the Supercomputer for Satellite Simulations and Data Assimilation Studies (S4). This O2R environment is critical for successful research-to-operations (R2O) transitions because it allows rigorous tracking, implementation, and merging of any changes necessary (to operational software codes, scripts, libraries, etc.) to achieve the scientific enhancement. So far, the S4 O2R environment, with close to 4,700 computing cores (60 TFLOPs) and 1,700-TB disk storage capacity, has been a great success and consequently was recently expanded to significantly increase its computing capacity. The objective of this article is to highlight some of the major achievements and benefits of this O2R approach and some lessons learned, with the ultimate goal of inspiring other O2R/R2O initiatives in other areas and for other applications.
publisherAmerican Meteorological Society
titleS4: An O2R/R2O Infrastructure for Optimizing Satellite Data Utilization in NOAA Numerical Modeling Systems: A Step Toward Bridging the Gap between Research and Operations
typeJournal Paper
journal volume97
journal issue12
journal titleBulletin of the American Meteorological Society
identifier doi10.1175/BAMS-D-14-00188.1
journal fristpage2359
journal lastpage2378
treeBulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 012
contenttypeFulltext


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