Global Weather Enterprise

Transcription

1 Global Weather Enterprise Data policy today and tomorrow Michael Staudinger Zentralanstaltfür Meteorologieund Geodynamik

2 Global Weather Enterprise

3 WMO Resolution Urges Members to: Members shall provide on a free and unrestricted basis essential data and products which are necessary for the provision of services in support of the protection of life and property and the well being of all nations, particularly those basic data and products, as, required to describe and forecast accurately weather and climate, and support WMO Programmes Those data and products from operational meteorological satellites that are agreed between WMO and satellite operators. (including data for severe weather and tropical cyclone warnings)

4 WMO Resolution Urges Members to: Members shall provide on a free and unrestricted basis essential data and products which are necessary for the provision of services in support of the protection of life and property and the well being of all nations, particularly those basic data and products, as, required to describe and forecast accurately weather and climate, and support WMO Programmes Those data and products from operational meteorological satellites that are agreed between WMO and satellite operators. (including data for severe weather and tropical cyclone warnings) (1) Six hourly surface synoptic data from RBSNs, (SYNOP, BUFR etc.) (2) All available in situ observations from the marine environment (3) All available aircraft reports, e.g. data in AMDAR, AIREP codes, etc. (4) All available data from upper air sounding networks, (TEMP, PILOT, TEMP, PILOT, SHIP) (5) All reports in CLIMAT/CLIMAT TEMP and CLIMAT SHIP/CLIMAT, etc. (6) Products distributed by WMCs and RSMCs to meet their WMO obligations

5 SWOT ANALYSIS Res 40 vs GWE Strength GOS well established Res40 Data exchange unparalleled in other sectors System details known to most partners Readiness for discussion and changes funding from new sources possible (e.g. development agencies etc.)

6 SWOT ANALYSIS Res 40 vs GWE Weakness Some partners not complying Large data gaps (e.g. RA I) No enforcement mechanisms of R40 et.al. No coherent mechanisms for private data Cooperation possibilities with private sector not fully exploited Only groups of countries sharing data R40: essential vs additional data: 1995

7 SWOT ANALYSIS Res 40 vs GWE Opportunities New technologies (EO data, IOT, funding for data gaps) Getting all data, Know How on a level playing field Optimize competition / cooperation possibilities Inform and help WMO members who dont deliver data WDX data market to be developed

8 SWOT ANALYSIS Res 40 vs GWE Threats Fragmentation of data landscape, standards, services Increased divide between privat vs public Monopolisation Lock in scenarios Weak regulators

9 Need for update of Resolution 40, 25, 60 R40 Assumption: Ressources to be available for essential data not given in meteorologically relevant regions (Tropics, Sub Sahara, Oceans... ) Missing: Incentives / support for countries with low GDP Info about WIGOS possibilities (Resolution vs Manuals) Help/ sanctions in cases of non-compliance

10 GWE the way forward 1. Observation data in data scarse areas (e.g. radiosondes tropics): Marketplace approach to secure funding, demonstrate improvement of numerical models and secure sustainable service delivery

11 GWE the way forward 1. Observation data in data scarse areas (e.g. radiosondes tropics): Marketplace approach to secure funding, demonstrate improvement of numerical models and secure sustainable service delivery 2. New types of satellite data (e.g. ROC) Marketplace approach to overcome the limitations of the present formulation of Res 40, incentivise investments from the private sector, avoid exclusivity of data for a sole provider and maximise usage

12 GWE the way forward 1. Observation data in data scarse areas (e.g. radiosondes tropics): Marketplace approach to secure funding, demonstrate improvement of numerical models and secure sustainable service delivery 2. New types of satellite data (e.g. ROC) Marketplace approach to overcome the limitations of the present formulation of Res 40, incentivise investments from the private sector, avoid exclusivity of data for a sole provider and maximise usage 3. Other data types (e.g. IOT) Marketplace approach to make data available to a user community as wide as possible and incentivise necessary research activities with the inclusion of the academic sector and wider parts of the research community

13 Which observation for which type of forecast? Nowcasting

14 1 day: obs needed

15 2 days: obs needed

16 3 days: obs needed

17 6 days: obs needed

18 2 weeks: obs needed

19 In situ data

20 Example: commercial ROC

21 AMDAR (EUMETNET) Source: EUMETNET

22 Data amount/value and provenance 50 Amount/value of data (rough guess only) Public data Private data

23 GDP per capita 2017

24 GDP per capita per country

25 GDP per country 2017 (IMF)

26 50 Infrastructure costs vs GDP (per capita) 0

27 Observation types & model performance Source: QJRMS 140, 2014

28 Setting market criteria Impact per observation Satellite data Radiosonde Bouys Ocean data (surface, deep ocean) Ground station mid latitude Ground station polar, tropic Aircraft (AMDAR) IOT

29 Copernicus

30 Copernicus

31 Landsat data policy

32 Landsat data policy Source: USGS Miller 2012

33 The value chain WMO Publ

34 Types of goods excludable Non-excludable Rival private common Non-rival club public

35 Types of goods excludable Non-excludable Rival Private House, car Common Fresh water, fish Non-rival Club Cable TV, toll road Public Clean air, knowledge

36 The value chain public Forecasting Quality WMO Publ

37 The value chain commercial public Forecasting Quality WMO Publ

38 The value chain exclusive commercial public Forecasting Quality WMO Publ

39 Txs 4 your attention!