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The Realization of GRAPES Model on China Meteorological Application Grid. Xuesheng YANG Chinese Academy of Meteorological Sciences China Meteorological Administration [email protected] 2005/09/16. Characteristics of Numerical weather prediction.

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the realization of grapes model on china meteorological application grid

The Realization of GRAPES Model on China Meteorological Application Grid

Xuesheng YANG

Chinese Academy of Meteorological Sciences

China Meteorological Administration

[email protected]

2005/09/16

characteristics of numerical weather prediction
Characteristics of Numerical weather prediction
  • Meteorology is one of the main components in the grid application
    • US:
      • LEAD (Linked Environment for Atmospheric Discovery)
      • MEAD (Modeling Environment for Atmospheric Discovery)
    • ECMWF: ECAccess
  • NWP system includes preprocessing, analysis, numerical model, post processing, visualization:
    • execution processes are dynamically connected
    • enormously complex even if run individually
    • Involves in data management, remote collaborative research, heavy computation, massive data and intensive services
  • to ensure the proper operation of a NWP:
    • massive computing resources needed
existed issues
Existed issues
  • tough issues meteorologists encountered:
    • organization of the NWP workflow and data
    • execution of model simulations
    • management of the resulting large volumes of data
    • subsequent data analysis
    • visualization
  • model developers and computing resources stationed in different locations
    • telephone, mobile, e-mail, …
      • inadequate for conducting a research project that involves in huge amount of simulations and extensive on-line discussions and consultations
    • Computing resources can’t satisfy the research requirements
      • divert researchers’ focus on how to acquire computing resources instead of addressing the scientific issues
existed computing resources at cma
Existed computing resources at CMA
  • Available operational computing resources:
    • IBM Cluster 1600
    • IBM SP
  • Available computing resources for research:
    • IBM
    • Clusters: Sunway, Dawning, Oscar, Ocean
      • CAMS
      • NMIC
      • Guangdong
      • Shanghai
      • Guangxi
      • etc.
  • do not get full utilized
    • Computing resources
    • manpower
2 china meteorological application grid cmag
2. China Meteorological Application Grid(CMAG)
  • grid portal
  • GridWeather
    • a NWP workflow control interface
  • GRAPES meso-scale model
  • user management sub-system
  • CVSExplorer
    • a code management system
  • visualization
slide6
ProjectManager

CodeExplorer

CVSManager

CVSExplorer

Portlets Modules

CMAGPortal Page

RainForecast

CityForecast

ElementForecast

PrecipitionObserved

Forecast Portlets

Portlets Modules

GridSphere Container

IE browser

LoginPortlet

ProfileManager

PortletApplication

LayoutManager

CredentialRecieve

JobSubmission

JobMonitoring

JobPosttreatment

FileManager

FileTransfer

ResourceBrowser

CredentialRequest

CredentialSign

CredentialDelete

GridUserMap

Tomcat5.28 Application Server

Base Portlets

GridWeatherportlets

Portlets Modules

GridUserPortlets

Portlets Modules

Ganglia

GridServices

Myproxy

GRAPESservice

Database Server

Mysql

CVS Server

Grid Software(GT2,GT3,GT4,GOS)

Job Scheduler (OpenPBS,LSF,Conder)

Grid Resources(Cluster,expensive instrument)

architecture of CMAG Portal

security and user management
Security and user management
  • provides a single-log-on access interface for all grid services and grid resources
  • authenticated users can access to computing, storage, data, software resources as well as all kinds of services
security and user management8
Security and user management
  • SimpleCA of Globus toolkit is adopted to ensure the security of the grid resources
    • based on GSI and supports X.509 inter-certification mechanism
  • CMAG Certification Authority signs each certificate
  • In actual implementation, a CA center at CMA is set up and CA distribution packages are installed at all CMAG nodes or provincial meteorological bureaus
  • User certifications managed by Myproxy library
cmag portal
CMAG Portal
  • Resource Access Portal
    • to access geographically distributed computing resources
  • NWP Products Browse Portal
    • to disseminate NWP products to the public and professional clients
  • Remote Collaborative Portal (RCP)
    • to offer a universal platform for scientists to develop NWP modules, to share source codes, to register modules within the grid and to perform NWP experiments.
cmag portal11
CMAG Portal
  • Globus 4.0 as the communication and tool-kit for collaborative research
  • authentification and grid-job management is performed based on Gridsphere Portal Framework and Java COG tool-kits.
job submission and resource monitoring
Job Submission and resource monitoring
  • based on the pre-wsrf-gram and wsrf-gram of Globus 4.0
  • Each grid resource has its own job scheduling software:
    • SSC:
      • PLATFORM’s LSF to perform job scheduling
    • Others:
      • OpenPBS
  • Ganglia to display dynamically the load of computing resource :
    • such as CPU load, availability of both memory and hard-disk, as well as network throughput
nwp executing control interface gridweather
NWP executing control interface --- GridWeather
  • NWP system involves complicated process control and massive parameters setting
  • traditional implementation method:
    • write a control routine
    • effective in local mode familiar with both every part of NWP system and system environment.
  • Gridweather:
    • based on Portlet including GRAM and GridFTP of CoG as well as Globus toolkit
slide16
interface for research: GARPES model improvement
  • to select the appropriate physical parameterization schemes
  • to designate forecast domain, available numerical schemes, etc.
slide17
Flowchart of GRAPES model improvement on CMAG

job-submission strategy : firstly, select the computing resources already with special experimental data, secondly, select machines that can run the GRAPES model

slide19
Flowchart of operational GRAPES meso-scale model on CAMG
  • job-submitting strategy:
  • selecting the computing resources that have had data already
  • selecting idle machines, then local machine, or any available high-performance computing capabilities machines.
cvsexplorer
CVSExplorer
  • NWP system upgrading
  • frequent modifications
  • diversity of program versions
  • intensive interactions between model developers and inter-comparisons between numerical experiments
  • it is necessary to create a suitable platform for joint NWP software development based on WinCVS
configuration of cmag
Configuration of CMAG
  • portal server:
    • deployed on a DELL server at CAMS, includes:
      • Web server Tomcat
      • Portal Framework Gridsphere
      • Web service software Java SOAP
      • grid application and development package CoG, GMETAD
      • web Front-end Ganglia
  • management node:
    • implemented at OSCAR Cluster at CAMS
  • Hierarchically structured MDS is installed
    • GIIS is available at each managing node and GRIS at other nodes.
slide24
Computing platform on CMAG

CADP: CMA CA Distributed Packages

STI: Shanghai Typhoon Research Inst.

real time weather forecasts
Real-time weather forecasts
  • GRAPES meso-scale model 30KM/15KM
    • Mainly for rain forecast
    • runs every day on CMAG
  • Real-time forecast products:
    • http://grid.cma.gov.cn:8080/
  • Also computing resources and NWP technique comparatively less developed regions can utilize the grid resources or even run the NWP models to satisfy their forecast service requirement:
    • Yantai
    • Qinghai
grapes meso scale model
GRAPES-Meso Scale model
  • new NWP system developed by Research Center for Numerical Prediction at CAMS
  • Features:
    • fully compressible primitive equations
    • switchable between hydrostatic and non-hydrostatic mode
    • semi-implicit and semi-Lagrangian advection schemes
    • latitude and longitude grid
    • horizontal Arakawa C grid
    • terrain-following coordinates
    • Charney-Phillips staggering vertically
    • physical parameterization package
slide27
prepocessing

Analysis

Forecast

Postprocessing

3D

Variation Analysis

GRAPES Model real-time

forecasts

Post-

processing

Forecast products

ATOVS Data

Preprocess

Initial

48hrs forecast

Quality control

visualization

Conventional

Data

preprocess

Global model lateral B.C.

Quality control

6hrs cycling

Flowchart of meso-scale GRAPES model on CMAG

conclusion
Conclusion
  • Distributed computing resources at Beijing, Shanghai, Guangdong and Guangxi aggregated
  • real-time GRAPES executions on CMAG feasible
  • a virtual collaborative R/D center established:
    • provides researchers at different locations with a common R/D environment aimed at further improvement of the GRAPES
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