Changes between Version 15 and Version 16 of udg/ecoms

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Mar 13, 2013 7:48:40 PM (9 years ago)
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 v15 Contents (under development): 1. [wiki:DataPortal Data Portal] [[PageOutline(1-3,,inline)]] {{{ #!comment 1. [wiki:DataPortal Data Portal] * [wiki:DataPortal/Technical Technical Details] * [wiki:DataPortal/Datasets Available Datasets] 2. [wiki:RPackage R Package for Data Access] * [wiki:RPackage/Authentication Authentication] * [wiki:RPackage/Functions Available datasets] * [wiki:RPackage/Examples Examples] }}} = Introduction and Motivation = #s.intro The impact activities on seasonal timescales involved in SPECS (http://www.specs-fp7.eu) and EUPORIAS (http://www.euporias.eu) projects require the use of different data sources (mainly seasonal forecasts, reanalysis, and observations). These activities include the calibration, downscaling, and modelling of sector-specific indices in agriculture, energy, health, etc., building on meteorological information. Typically, only a reduced subset of surface variables (precipitation, temperatures, mean sea level pressure, etc.) or in a reduced number of vertical levels (circulation and termodynamic drivers at, e.g., 850, 500, 200 hPa) is required for these activities.  The ''SPECS-EUPORIAS Data Portal'' has been established by the '''Santander Meteorology Group (UC-CSIC)''' to gather the relevant information from existing datasets in order to provide a unique homogenized access to data for the SPECS and EUPORIAS partners (in particular for impact-users). The ''SPECS-EUPORIAS Data Portal'' is based on a THREDDS data server providing metadata and data access using OPeNDAP and other remote data access protocols. Moreover, since the R language (http://www.r-project.org) has been adopted for some key tasks in these projects (including the development of comprehensive validation and statistical-downscaling packages) a user-friendly R package has been developed to explore and access the data portal. This package can be used in R programs to remotely access subsets of data, thus reducing the burden of data access (versions for Python and Matlab are also available under request). This package will be continuously updated (keep informed at the documentation URL above) as part of the data management activities to build a data bridge for impact users and for the R developments to be done in these projects. This document briefly describes the current state of the data portal, which has initially focused on data from the ''ECMWF's System4 seasonal model'', as agreed in the downscaling parallel session of the kick-off meeting. = The THREDDS Data Server = #s.thredds The ''SPECS-EUPORIAS Data Portal'' is based on a password-protected THREDDS data server providing metadata and data access to a set of georeferenced atmospheric variables using OPeNDAP and other remote data access protocols. The variables names, units and additional metadata follow the [http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.4/cf-conventions.html CF convention]. The variables are spatial grids based on multidimensional arrays of indexed values, following Unidata's ''_Coordinate convention'' ([http://www.unidata.ucar.edu/software/netcdf-java/reference/CoordinateAttributes.html Coordinate Attributes] and [http://www.unidata.ucar.edu/software/netcdf-java/tutorial/GridDatatype.html Grid data types]). Typically the data portal will include information at a daily resolution, but monthly-aggregated values could be also provided in some cases due to data limitations (in particular, ''Mètèo-France'' and ''Met Office'' have agreeed to provide monthly mean hindcasts for their use by the ''SPECS'' and ''EUPORIAS'' partners). In general, the data available will be typical surface variables (e.g. precipitation and near-surface temperature), although several variables (e.g. geopotential and temperature) on pressure levels will also be  stored for the statistical downscaling activities. The data gathering activities have initially focused on the ''ECMWF System4 seasonal model''. The Meteorological Archival and Retrieval System (MARS) is the main repository of meteorological data at the ''ECMWF'' (European Centre for Medium-Range Weather Forecasts). It contains terabytes of operational and research data as well as data from special projects ([http://www.ecmwf.int/services/archive/ MARS service]). The large amount of information stored and the inherent complexities of data access, download and post-processing is a first shortcoming for a flexible use of these datasets by a large number of partners. To overcome this issue, a reduced subset of surface variables (http://www.ecmwf.int/products/changes/system4/technical_description.html#description) (precipitation, temperatures and mean sea level pressure) have been downloaded from MARS (a colection of GRIB-1 files) at 0.75º spatial resolution and made available throught the ''SPECS-EUPORIAS data portal''. The downloaded data has been exposed as three different virtual datasets using TDS: * '''System4 seasonal range (15 members)''': There are twelve initializations (hereafter called runtimes) per year (the first of January, February, ...) running for 7 months (hereafter called simply times). An ensemble of 15 members is available for the whole 1981-2010 period. * '''System4 seasonal range (51 members)''': There are only four runtimes per year (the first of  February, May, August and November) and the forecasts run for 7 months. An ensemble of 51 members is available for the whole 1981-2010 period. * '''System4 annual range (15 members)''': As in the previous case, there are four runtimes per year, but the forecasts run for 13 months. An ensemble of 15 members is available for the whole 1981-2010 period. Data gathering activities will next move to the CFS (http://cfs.ncep.noaa.gov) version 2 hindcast, developed at the '''Environmental Modeling Center at NCEP'' and also to reanalysis and observational datasets. Although the TDS provides a web interface to explore and access the datasets (shown in [#s.web.access web access section]), it is strongly recommented the use of OPeNDAP (a.k.a. DODS) client libraries to remotely access the data from scientific computing environments (R, Matlab, Python, etc.). For instance, the R function provided in this tutorial is based on the ''NetCDF Java'' OPeNDAP client (http://www.unidata.ucar.edu/software/netcdf-java/documentation.htm), using the rJava R package (a similar approach is been also made for the Matlab implementation). Alternatively, the most recent ''NetCDF library'' versions provide access to OPeNDAP datasets (this is the solution for the Python implementation). In the following, we show a simple example of data access using the R package developed as part of the data portal. In particular the ''System4'' datasets can by directly accessed using the loadSystem4 function, allowing the retrieval of slices for a particular variable in any of the dataset dimensions (member/space/runtime/time). Note that a more ellaborated worked example using R is shown in the [#Appendix.rexample R example section].  Moreover, for a better understanding of the datasets structure, the use of the web interface for the OPeNDAP  service is also illustrated [#s.web.access web access section].