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MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-serviceClimate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.
Document ID
20140013036
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Schnase, John L.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Duffy, Daniel Quinn
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Tamkin, Glenn S.
(Computer Sciences Corp. Greenbelt, MD, United States)
Nadeau, Denis
(Computer Sciences Corp. Greenbelt, MD, United States)
Thompson, John H.
(Patuxent Technology Partners, LLC Fairfax Station, VA, United States)
Grieg, Christina M.
(George Mason Univ. Fairfax, VA, United States)
McInerney, Mark A.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Webster, William P.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
October 15, 2014
Publication Date
January 1, 2014
Subject Category
Meteorology And Climatology
Computer Programming And Software
Report/Patent Number
GSFC-E-DAA-TN10700
Report Number: GSFC-E-DAA-TN10700
Funding Number(s)
CONTRACT_GRANT: NNG13HQ01C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Data Analytics
MapReduce
Hadoop
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