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Socio-economic Benefits of Hydrometeorological and Climate Services

This presentation explores the economic effects and benefits of hydrometeorological activities, including hazard evaluation, satellite information, and economic benefit evaluation.

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Socio-economic Benefits of Hydrometeorological and Climate Services

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  1. 5.4 Improved understanding of the socio-economic benefits of hydrometeorological and climate services5.4.1 Estimated economic effect and benefits of hydrometeorological activities A. Korshunov National Oceanic and Atmospheric Administration, November 2011

  2. Main topics of presentation 1. Hazardous and unfavourable weather events that caused economic and social damage in Russia in 1991-2010. 2. Scientific and methodical foundations of benefit evaluation. 3. Economic benefit and effectiveness of using hydrometeorological information in the Hydrometeorological Service of Russia. 4. Evaluation of the contribution and usefulness of satellite information in forecasting convection processes.

  3. Distribution of hazardous weather events that caused social and economic damage in the period 1991-2010 by years(frequency of occurrence in the 20-year period is 259)METEO.RU

  4. Distribution of hazardous events in the period 1991-2010 by seasons(cold seasons: November and December of the previous year; January, February and March of the current year)

  5. Average monthly number of hazardous events that caused economic damage in the period 1991-2009 compared with that in 2010

  6. Number of hazardous events (by types) in 2010 compared with the monthly average in the period 1991-2009(1 – strong wind, hurricane, squall, spout. dust storm; 2 – blizzard, heavy snowfall, a mix of snow and rain, slush build-up, glaze, glazed frost; 3 – heavy rain, long-lasting rain, shower, hail, thunderstorm; 4 – severe frost, freezing, strong heat, sharp temperature change; 5 – spring flood, rain flood, flooding, surge, ice jam; 6-avalanche, mudflow; 7 – atmospheric and soil drought, hot dry wind; 8 – fire hazard emergency; 9 – other)

  7. OJ-meteo database menu

  8. Economic benefit evaluation Territorial administrations of the Hydrometeorological Service (UGMS) are the main component of the Roshydromet system that provides hydrometeorological services for economic sectors and people. UGMSs determine the size of the economic benefit (EB). RIHMI-WDC is involved in methodical management of UGMSs in EB evaluation, EB data collection and EB data integration.

  9. EB evaluation by types of documents using UGMS evaluation procedures

  10. Economic sectors that have procedures developed until 2001 Agriculture; Forestry; Construction; Housing and utilities; Transport (road, railroad, sea and river transport); Public road system; Aviation; Marine sector; Industry; Water facilities; Communication.

  11. General Roshydromet information for 2009 with respect to 2008

  12. Slide title In the period 11-13 September 2007 a workshop was held in RIHMI-WDC with the participation of NOAA and Roshydromet experts NOAA delegation: 1. Rodney Weiher, NOAA chief economist; 2. Jeffery Lazo, NCAR director, economist.

  13. The major objective of the cooperation is stated as follows “To make people to be better informed of and understand the methods and approaches to the economic analysis and research, risk analysis, as well as the contribution this analysis could make to improving the planning and the implementation of the routine activity of Hydrometeorological Services, including the cost-effectiveness analysis, the value engineering, the analysis of investments, and the risk assessment”.

  14. Harmonization of methodologies used by Roshydromet to estimate the economic benefit with those used by other Ministries A reference method of the EB quantitative evaluation and economic effectiveness of using hydrometeorological forecasts: methodological and conceptual foundations.(Confirmed by Roshydromet on 4 August 2008).

  15. Reference procedure based on the generation of the conjugation matrix is used to evaluate economic effectiveness

  16. Reference procedure based on the generation of the economic loss matrix is used to evaluate economic effectiveness

  17. Major formulae of the reference method (mean Bayesian losses)

  18. Major formulae of the reference method Э = N [( ) – Зпп], whereis the proportional factor of participation of the Hydrometeorological Service in obtaining the effect from forecasts ( = 0,71),Nis the total number of weather forecasts for the given user for the period chosen, Зпп is the cost of forecasts that is considered as pre-production losses. Р =Э/(NЗпп)

  19. Harmonization of methodologies used by Roshydromet to estimate an economic effect with those used by other Ministries METHODOLOGY OF ESTIMATING ECONOMIC EFFECT OF HYDROMETEOROLOGICAL INFORMATION FOR THE PUBLIC ROAD SYSTEM.(Confirmed by Roshydromet on 14 May 2009).

  20. Economic benefit (in thousands of rubles) from using hydrometeorological information on federal routes for the cold season 2007-2008 was as follows:

  21. Harmonization of methodologies used by Roshydromet to estimate an economic effect with those used by other Ministries Methodology of numerical estimation of economic effect and benefits (prevented losses) of meteorological forecasts for operation of power transmission systems. (Confirmed by Roshydromet on 2 March 2009). Э = 2.09 million rubles Р = 11.5

  22. Harmonization of methodologies used by Roshydromet to estimate the economic benefit with those used by other Ministries Procedure of estimating the economic benefit and effectiveness of spring frost forecasts. (Confirmed by Roshydromet on 2 March 2010). For spring wheat, Э = 9.5million rubles Р = 85.45

  23. Criteria to calculate economic usefulness Total success rate is the ratio of the number of verified forecasts to the total number of forecasts Obukhov accuracy of forecasts, i.e. the number of accurate and successful forecasts, given the known frequency of weather phases, varies between 1 and -1 Total success rate of random forecasts Bagrov reliability, i.e. increment of the total success rate of the forecasts estimated (as compared with random forecasts) to the maximum possible success rate

  24. Khandozhko weighted success rate, i.e. the success rate that includes the weighted “price” of the verified forecasts, with the weights of errors-gaps and errors-insurances being taken into account Gottman-Kruskal measure

  25. Economic value of hazardous weather event forecasts (based on data from Saint-Petersburg)

  26. Economic value of thunderstorm forecasts (based on data from Samara)

  27. Quantitative estimates of economic value of satellite information for forecasting of some hydrometeorological events have been obtained • Contribution of satellite information to various criteria of economic value varies from 15% to 60%

  28. THANK YOU! korshunov@meteo.ru

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