Introduction

NASA's Climate Data Services are presented in this overview. The Introduction illustrates the overall project and it's goals. The MERRA Motivation chapter summarizes why MERRA was targeted and the benefits it provides. The Components section describes the moving parts.

Climate 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 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 the Big Data challenges in this domain.

MERRA-Motivation

MERRA Analytic Services (MERRA/AS) is an example of CAaaS built on this principle. MERRA/AS enables MapReduce analytics over NASA’s 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. MERRA/AS 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 MERRA/AS has been demonstrated in several applications.

Components

The Climate Data Services are built upon a general-purpose specification that defines the Application Programming Interface (API). This API, which is detailed in the CDS API section, formalizes the interactions between the CDS services and its consumers. The API is currently implemented by two services including the MERRA Analytic Service and the Persistence Service, which are each described in detail separately. In effect, these services are built on top of the CDS API. As future services are added, they will also adhere to this API in order to provide a standard access strategy.

CDS services are available by accessing the CDS API, which can be executed using either direct web service calls, a Python script of sequential commands, or a full featured Python application. The CDS client package contains everything needed to make CDS requests.