PracJcal on Data Handling BEAT Toolbox

Prac%cal on Data Handling BEAT Toolbox S.V. Niemeijer S[&]T Introducing BEAT BEAT: the Basic Envisat/ERS Atmospheric Toolbox Goal: to provide the necessary soIware to support scien%fic analysis of atmospheric data. BEAT supports three layers of func%onality: –  CODA –  BEAT-­‐II –  VISAN direct product interface simplified data interface visualiza4on & analysis applica4on For this course, we will focus on BEAT-­‐II and VISAN. CODA •  Single interface to read any data from a product •  Very direct mapping to the data in a product •  Requires user to have knowledge about the product structure •  Func%on interfaces for C, Fortran, Java, Python, IDL, and MATLAB •  Useful command line tools CODA codadd codacheck codaeval Fortran interface Python interface Java interface IDL interface MATLAB interface codafind codadump codacmp CODA C library XML backend Mission #1 codadef netCDF backend CDF backend Mission #2 codadef GRIB backend HDF4 backend HDF5 backend HDF4 library Mission #3 codadef RINEX backend SP3 backend HDF5 library BEAT-­‐II Why two different interfaces? •  Many data products have a very complicated structure that reflect the way data-­‐processors work, not the way end-­‐users look at the data. •  Correct matching of measured spectra/retrievals to geoloca%on (“ground pixels”) can be hard to get right. •  For typical analysis work, only a frac%on of the data within the file is useful. •  It is difficult to compare data from different instruments. •  BEAT-­‐II addresses these issues by providing a simplified (but s%ll valid!) view on the data. BEAT-­‐II •  Only one call needed to ingest the most important data from a single product or mul%ple products •  Ingest product data into ‘flat’ BEAT-­‐II records •  Powerful inges%on filter op%ons to determine which parameters to ingest and to put restric%ons on %me, loca%on, etc. •  BEAT-­‐II records use na%ve data type for each interface (e.g. ‘struct’ for MATLAB/IDL, ‘object’ for Python) •  Each field corresponds with a specific scien%fic parameter •  Fields use standardized naming conven%on and provide data in standardized units, thus allowing easy comparison BEAT-­‐II Fortran interface Python interface Java interface IDL interface MATLAB interface beatl2dump BEAT-­‐II C library ACE-­‐FTS module Bremen
module GOMOS module GOME module GOME-­‐2 module GOSAT module HIRDLS module HITRAN module IASI module MIPAS module MLS module OMI module OSIRIS module SCIAMACHY SMR module TEMIS module TES module module CODA C library HDF4 library HDF5 library VISAN •  Ingest data using CODA and BEAT-­‐II •  Python language for command input and performing calcula%ons and manipula%ons •  With one func%on call, create interac%ve 2D and World plot visualiza%ons of your data •  Open Source and Cross-­‐Plaoorm: Windows, Linux, and Mac OS X. BEAT Future New features coming in 2015 and beyond •  BEAT-­‐II -­‐> HARP –  automa%c unit and parameter conversion –  ver%cal profile calcula%ons (smoothing, resampling, integra%on) –  colloca%on •  New missions: – 
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Sen9nel 5P NPP Suomi Atmospheric CCI Aeolus EarthCARE