Reflections on the theme of classifying, documenting and exchanging meteorological data, and some additional comments on agro meteorological and biological.

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Presentation transcript:

Reflections on the theme of classifying, documenting and exchanging meteorological data, and some additional comments on agro meteorological and biological data sets. Tor Håkon Sivertsen The Norwegian Crop Research Institute

The weather systems on the planet earth do not respect the borders put up by the nations. The exchange of meteorological data sets connected to the man made systems for making measurements and models for predicting the global weather is a concern of international character.

I will look at a few related subjects: Classifying phenomena connected to weather and climate. Existing systems of exchanging meteorological data What challenges of exchanging data will appear in the future connected to real time exchange of data between monitoring systems and models. The place of agro meteorological and biological models in this. The different systems for making observations.

Classification of meteorological phenomena and climate Classification of clouds (Luke Howard) Classification in synoptic meteorology Classification of in cloud physics, tropical meteorology, physical meteorology etc. Classification of climate (Wladimir Köppen in the years )

The idea of using the modern tool of object oriented analysis when constructing classes of meteorological phenomena in numerical models of weather and climate( COST718) The basic idea is that in each class or sub class of a phenomenon quantitative parameters/ attributes is attached to the phenomenon. Then we have a numerical sub model or a numerical model.

The existing systems of exchanging meteorological data sets in the frame of WMO( World Meteorological Organisation): CREX (Character form for the Representation and EXchange of data) BUFR (Binary Universal Form for Representation of meteorological data). Gridded data sets, called GRIB ( ‘ GRIdded Binary ’ ).

The CREX/BUFR system A BUFR-message consist of six sections(of octets): ‘ Indicator section ’ ‘ Identification section ’ ‘ Optional section ’ ‘ Data description section ’ ‘ Data section ’, ‘ End section ’. The metadata of the BUFR-system is contained in the sections 1,2 and 3. The metadata is interpreted by several tables information about the ‘ category ’ of the data and the types of quantitative information considered.

GRIB-system A GRIB-record consists of six sections, ‘ Indicator section ’, ‘ Product Definition Section (PDS) ’ containing metadata on the parameters considered, ‘ Grid Description Section ’ containing information on the grid used (type projection of mapping used) etc., ‘ Bit Map Section(BMS) – optional ’ contains information of parameter fields not defined in certain subsystems of the gridded model by a bit-map- system, ‘ Binary Data Section (BDS) ’, ‘ End section ’ ‘ 7777 ’ (human readable indication of the end of the record)

The metadata of the ‘ GRIB ’ - system is mainly contained in section number ‘ 1 ’, and section number ‘ 2 ’ and the interpretation is given in several tables. The ‘ GRIB ’ -system is tailored for representation and exchange of the content of numerical weather prediction models.

The metadata contained in the ‘ BUFR ’ and ‘ GRIB ’ -systems is called meteorological elements. According to ‘ International Meteorological Vocabulary ’ a ‘ meteorological element ’ is defined in the following manner: ’ Atmospheric variable which characterizes the state of the weather at a specific place at a particular time (e.g. air temperature, pressure, wind, humidity, thunderstorm and fog) ’.

Attached to ‘ BUFR ’ and ‘ GRIB ’ there are several tables giving the interpretation of the meteorological elements. This classification system consists of a mixture of phenomena and parameters describing the phenomena, and the system is very flexible and has great scope. But my message is: This meta data part ought to be reconsidered according to the ideas put up above.

The term ‘ parameter ’ is often used to describe a quantitative property of the atmosphere ( air pressure, air temperature, wind velocity, global radiation etc.) The term ‘ parameter ’ is not defined in The meteorological glossary, but the term ‘ parametrization ’ is defined in the following manner: ‘ Approximate representation of subgrid- scale processes in a numerical model in terms of variables which are explicitly calculated ’.

The use of the term ‘ parameterisation ’ could be more general. When a weather phenomenon is described by attaching quantitative measurable attributes to it we call it ‘ parameterisation ’. The parameterisation of the phenomena then has to be different on the different scales.

The work on quality and availability of data made in COST718 ACTION In agro meteorological contexts the need of exchange of data often is for modelling purposes. Therefore the need for metadata and documentation is connected to the modelling (crop growth as well as crop protection/ warning systems)

A Documentation System for Parameters (a) Measured (b) In Models Name of the parameter Unit Defintion Method(s) for measurement Representativeness CREX/BUFR descriptors Name of the parameter Unit Defintion Representativeness in model considered Representativeness of other models CREX/BUFR descriptors

I think this meta data discussion, and the discussion on exchange of agro meteorological and biological data ought to be put in the frame set by the planning of a new COST action and the work in the frame of work led by WMO and connected to weather hazards, see THORPEX-project, A global atmospheric research program.

A new COST action of agro meteorology probably will get the name: ’ CLIMATE CHANGE AND IMPACT OF METEOROLOGICAL HAZARD ON AGRICULTURE ’. In this connection I refer to the THORPEX- program of WMO, see session ‘NP 5.04 Weather hazards reduction(THORPEX)’ at the EGU-meeting in Vienna in April 2005.

What is probably possible to develop is a system for exchange of data and information in almost real time between the observation systems on the ground (automated stations, weather radar systems etc.) and the information from the satellites and the different numerical weather prediction systems running.

A question often raised to meteorologists is the following question: Is it possible to replace the old ground based meteorological stations with the measurements of the meteorological parameters by remote sensing equipment like weather radars and satellites?

The work on ‘ homogenisation ’ of long data series of meteorological data is connected to the observing systems. In studies on global change and climate change it is important to be able to refer to long homogenous series of meteorological data.

My conclusion is very short: When looking at BUFR and GRIB, what could be considered is making some sort of parallel work of extending the biological and agro meteorological models to use the BUFR and GRIB-protocols, but at the same time take a look at the metadata systems of GRIB and BUFR first to see if the classification systems may be constructed in a more logical way using methods from object oriented analysis of the modern IT-world?

Thank you very much!