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Dean N. Williams
,
V. Balaji
,
Luca Cinquini
,
Sébastien Denvil
,
Daniel Duffy
,
Ben Evans
,
Robert Ferraro
,
Rose Hansen
,
Michael Lautenschlager
, and
Claire Trenham

Abstract

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.

Full access
Eric Guilyardi
,
V. Balaji
,
Bryan Lawrence
,
Sarah Callaghan
,
Cecelia Deluca
,
Sébastien Denvil
,
Michael Lautenschlager
,
Mark Morgan
,
Sylvia Murphy
, and
Karl E. Taylor

The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. Here we describe a pilot community initiative to collect and make available documentation of climate models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). It is expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.

Full access
Gerhard Theurich
,
C. DeLuca
,
T. Campbell
,
F. Liu
,
K. Saint
,
M. Vertenstein
,
J. Chen
,
R. Oehmke
,
J. Doyle
,
T. Whitcomb
,
A. Wallcraft
,
M. Iredell
,
T. Black
,
A. M. Da Silva
,
T. Clune
,
R. Ferraro
,
P. Li
,
M. Kelley
,
I. Aleinov
,
V. Balaji
,
N. Zadeh
,
R. Jacob
,
B. Kirtman
,
F. Giraldo
,
D. McCarren
,
S. Sandgathe
,
S. Peckham
, and
R. Dunlap IV

Abstract

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users.

The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.

Full access
P. A. Francis
,
A. K. Jithin
,
J. B. Effy
,
A. Chatterjee
,
K. Chakraborty
,
A. Paul
,
B. Balaji
,
S. S. C. Shenoi
,
P. Biswamoy
,
A. Mukherjee
,
P. Singh
,
B. Deepsankar
,
S. Siva Reddy
,
P. N. Vinayachandran
,
M. S. Girish Kumar
,
T. V. S. Udaya Bhaskar
,
M. Ravichandran
,
A. S. Unnikrishnan
,
D. Shankar
,
A. Prakash
,
S. G. Aparna
,
R. Harikumar
,
K. Kaviyazhahu
,
K. Suprit
,
R. V. Shesu
,
N. Kiran Kumar
,
N. Srinivasa Rao
,
K. Annapurnaiah
,
R. Venkatesan
,
A. S. Rao
,
E. N. Rajagopal
,
V. S. Prasad
,
M. D. Gupta
,
T. M. Balakrishnan Nair
,
E. P. R. Rao
, and
B. V. Satyanarayana

Abstract

A good understanding of the general circulation features of the oceans, particularly of the coastal waters, and ability to predict the key oceanographic parameters with good accuracy and sufficient lead time are necessary for the safe conduct of maritime activities such as fishing, shipping, and offshore industries. Considering these requirements and buoyed by the advancements in the field of ocean modeling, data assimilation, and ocean observation networks along with the availability of the high-performance computational facility in India, Indian National Centre for Ocean Information Services has set up a “High-Resolution Operational Ocean Forecast and Reanalysis System” (HOOFS) with an aim to provide accurate ocean analysis and forecasts for the public, researchers, and other types of users like navigators and the Indian Coast Guard. Major components of HOOFS are (i) a suite of numerical ocean models configured for the Indian Ocean and the coastal waters using the Regional Ocean Modeling System (ROMS) for forecasting physical and biogeochemical state of the ocean and (ii) the data assimilation based on local ensemble transform Kalman filter that assimilates in situ and satellite observations in ROMS. Apart from the routine forecasts of key oceanographic parameters, a few important applications such as (i) Potential Fishing Zone forecasting system and (ii) Search and Rescue Aid Tool are also developed as part of the HOOFS project. The architecture of HOOFS, an account of the quality of ocean analysis and forecasts produced by it and important applications developed based on HOOFS are briefly discussed in this article.

Free access
P. A. Francis
,
A. K. Jithin
,
J. B. Effy
,
A. Chatterjee
,
K. Chakraborty
,
A. Paul
,
B. Balaji
,
S. S. C. Shenoi
,
P. Biswamoy
,
A. Mukherjee
,
P. Singh
,
B. Deepsankar
,
S. Siva Reddy
,
P. N. Vinayachandran
,
M. S. Girish Kumar
,
T. V. S. Udaya Bhaskar
,
M. Ravichandran
,
A. S. Unnikrishnan
,
D. Shankar
,
A. Prakash
,
S. G. Aparna
,
R. Harikumar
,
K. Kaviyazhahu
,
K. Suprit
,
R. V. Shesu
,
N. Kiran Kumar
,
N. Srinivasa Rao
,
K. Annapurnaiah
,
R. Venkatesan
,
A. S. Rao
,
E. N. Rajagopal
,
V. S. Prasad
,
M. D. Gupta
,
T. M. Balakrishnan Nair
,
E. P. R. Rao
, and
B. V. Satyanarayana
Full access