1 / 14

Ivan Tsonevsky ,

Heavy Precipitation Forecasting using Neural Networks. A Flash Flood Event in Bulgaria in s ummer 2005 (case study). Ivan Tsonevsky , Weather Forecasting Department, National Institute of Meteorology and Hydrology , BULGARIA. Constanta, 20-26 August, 2006. ANNs in meteorology.

anitra
Download Presentation

Ivan Tsonevsky ,

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Heavy Precipitation Forecasting using Neural Networks. A Flash Flood Event in Bulgaria in summer 2005 (case study) Ivan Tsonevsky, Weather Forecasting Department, National Institute of Meteorology and Hydrology, BULGARIA Constanta, 20-26 August, 2006

  2. ANNs in meteorology ANNs for classification problems: • MLP; • RBF; • Kohonen; • PNN; • Linear.

  3. Input Hidden layer Output MLP

  4. Novo selo Silistra Vidin Ruse Lom Oriahovo Belene Svishtov Shabla Dobritch Razgrad Kneja Montana Pleven Kaliakra Vratza Varna Lovetch V. Turnovo Dragoman Sliven Sofia Karnobat Kazanluk Burgas Kiustendil Pazardjik Chirpan Plovdiv Elhovo Ahtopol Blagoevgrad Kurdjali Sandanski ANNs for precipitation forecasts Bulgaria was divided into 6 regions.

  5. ANNs for precipitation forecasts A number ofMLPs were trained: • winter - threshold = 10 mm/12h • summer - threshold = 15 mm/12h • training set: 1998-2004 • 27 input variables from NWP models • 1 output – class of the case (above or below the threshold)

  6. Case study • 1-4.07.2005 Geopotential height at 500 hPa 1.07/00 UTC 2.07/00 UTC 4.07/00 UTC 3.07/00 UTC

  7. Case study • 1-4.07.2005 Mean sea level pressure 2.07/00 UTC 1.07/00 UTC 3.07/00 UTC 4.07/00 UTC

  8. Case study • 1-4.07.2005 Accumulated precipitation amount

  9. 207 % 228 % 77 % 80 % 144 % 79 % 167 % 249 % 128 % 43 % 80 % 149 % 169 % 24 % 169 % 124 % 30 % 128 % 40 % 58 % 138 % 261 % 110 % 77 % 47 % 24 % 292 % 150 % 79 % 194 % 85 % 102 % 16 % 21 % 91 % 30 % Case study • 1-4.07.2005 Precipitation rate: Pacc.(1-4.07)/Pmonthly mean

  10. Central part of North Bulgaria; Northeast of Bulgaria; Central part of South Bulgaria. Case study Floods occured and many damages were reported. The most affected areas were:

  11. Case study ANNs:

  12. Case study ANNs:

  13. Case study ANNs:

  14. Conclusions • Neural Network techniques can be applied successfully in Meteorology for classification, analysis and weather forecasts. • In Bulgaria a number of Neural Networks have been trained successfully for regional classification of precipitation events during the cold and the warm half of the year. • Satisfactory results obtained for the extremely wet 2005 by using Neural Networks confirm the benefits from the usage of Neural Networks techniques when severe weather warnings ought to be issued.

More Related