Identification

Title

Parallel implementations of ensemble data assimilation for atmospheric prediction [presentation]

Abstract

Numerical models are used to find approximate solutions to the coupled nonlinear partial differential equations associated with the prediction of the atmosphere. The model state can be represented by a grid of discrete values; subsets of grid points are assigned to tasks for parallel solution. Data assimilation algorithms are used to combine information from a model forecast with atmospheric observations to produce an improved state estimate. Observations are irregular in space and time, for instance following the track of a polar orbiting satellite. Ensemble assimilation algorithms use statistics from a set (ensemble) of forecasts to update the model state. All the challenges of heterogeneous grid computing and partitioning for atmospheric models are in play. In addition, the heterogeneous distribution of observations in space and time is a further source of irregular computing load while ensembles lead to increased storage and an additional communication pattern. Adjacent observations cannot be assimilated simultaneously leading to a mutual exclusion scheduling problem that interacts with the grid partitioning communication patterns and load balancing. Simulations of efficient approaches to the scheduling and grid partitioning problem for ensemble assimilation are presented. Prospects for implementation on accelerator architectures are also discussed.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7c82bzr

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2013-12-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact