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DIRECTION GENERALE DE LA METEOROLOGIE NATIONALE (DGMN)

DIRECTION GENERALE DE LA METEOROLOGIE NATIONALE (DGMN). THEME DATA RESCUE Présented by: - LAOGBESSI T-T Egbèsem Togo meteorological Service Lomé / Togo. PLAN. I ) INTRODUCTION II) HISTORICAL WEATHER DATA BACKUP III) NEXT BANJUL WORKSHOP IV) ANALYSIS OF CLIMATE INDICES

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DIRECTION GENERALE DE LA METEOROLOGIE NATIONALE (DGMN)

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  1. DIRECTION GENERALE DE LA METEOROLOGIE NATIONALE(DGMN) • THEME • DATA RESCUE • Présented by: - LAOGBESSI T-T Egbèsem Togo meteorological Service Lomé / Togo

  2. PLAN • I ) INTRODUCTION • II) HISTORICAL WEATHER DATA BACKUP • III) NEXT BANJUL WORKSHOP • IV) ANALYSIS OF CLIMATE INDICES • V) CONCLUSION

  3. INTRODUCTION • Geography of Togo • Togo is a small West African nation. It borders the Bight of Benin in the south; Ghana lies to the west; Benin to the east; and to the north Togo is bound by Burkina Faso. Togo lies mostly between latitudes 6° and 11°N, and longitudes 0° and 2°E.

  4. INTRODUCTION • Climate of Togo • The climate is generally tropical with average temperatures ranging from 27.5 °C on the coast to about 30 °C in the northernmost regions, with a dry climate and characteristics of a tropical savanna. To the south there are two seasons of rain (the first between April and July and the second between (September and November), even though the average rainfall is not very high.

  5. INTRODUCTION • The Meteorological Service of Togo has a network composed of 9 synoptic stations, 17 climatological stations and more than 200 rainfall stations.

  6. INTRODUCTION LOCALISATION OF THE STATIONS

  7. HISTORICAL WEATHER DATA BACKUP

  8. HISTORICAL WEATHER DATA BACKUP • Meteorological data in our possession are 9from 1921. The observation of some data goes back to 1884 but kept in Germany.All data are in paper format (TCM (monthly climatological table), rainfall records etc..).

  9. HISTORICAL WEATHER DATA BACKUP • The first backup was made by ORSTOM (Office of Scientific and Technical Research Overseas, now IRD Institute of Research for Development ). It has published two volumes of rainfall data: the first, from the creation of the stations until 1965, and the second from 1966 to 1981

  10. HISTORICAL WEATHER DATA BACKUP • Through the project R3S (Research Network of Resistance in the Sahel) in 1987, with the software PLUIETP, seizures of rainfall for all the stations were made from the creation until 2000 • Data of temperature, humidity and insolation (sunshine) of 9 synoptic stations were seized from 1961 to 2000

  11. HISTORICAL WEATHER DATA BACKUP • Through the DARE project in 1987, with the help of the Royal Meteorological Institute of Belgium, we have microfilmed records of 76 stations (synoptic, climatological and rainfall) from the date of their creation until 1987. • Some projects do not give us satisfaction, like CLICOM and CLIDATA. • To date, we have a large amount of data not scanned. We seek funding to put them on magnetic support for backup.

  12. NEXT BANJUL WORKSHOP

  13. NEXT BANJUL WORKSHOP • At workshop in Banjul in december 2011, with the software RClimDex, we used rainfall and temperature for calculating climate index. This allowed us to resume daily rainfall data and temperature from 1961 to 2011 of 9 synoptic stations of the country for which we did quality control and diagnose the particular entry errors. • RClimDex allowed us to identify the climatic trend in our country that I will show you

  14. ANALYSIS OF CLIMATE INDICES

  15. ANALYSIS OF CLIMATE INDICES • APPLIED STATISTICS ON CLIMATE INDICES • If p-value < 0.05, we say that the trend:1)- Is increasing or decreasing and significant at 95% confidence2)- With a risk of error of 5%

  16. ANALYSIS OF CLIMATE INDICES • 1) EVOLUTION OF PRECIPITATIONS

  17. EVOLUTION OF PRECIPITATIONS : LOME P-VALUE = 0.558 SLOPE ESTIMATE = - 1.413

  18. EVOLUTION OF PRECIPITATIONS : ATAKPAME P-VALUE = 0.672 SLOPE ESTIMATE = 1.115

  19. EVOLUTION OF PRECIPITATIONS : SOKODE P-VALUE = 0.014 SLOPE ESTIMATE = - 5.935

  20. EVOLUTION OF PRECIPITATIONS : KARA P-VALUE = 0.533 SLOPE ESTIMATE = - 1.225

  21. EVOLUTION OF PRECIPITATION S: MANGO P-VALUE = 0.198 SLOPE ESTIMATE = - 1.759

  22. ANALYSIS OF CLIMATE INDICES • 2) EVOLUTION OF TEMPERATURES

  23. EVOLUTION OF TEMPERATURES LOME TMAX LOME TMin P-VALUE = 0 P-VALUE = 0.001 SLOPE ESTIMATE = 0.063 SLOPE ESTIMATE = 0.042

  24. EVOLUTION OF TEMPERATURES ATAKPAME TMin ATAKPAME TMAX P-VALUE = 0 P-VALUE = 0 SLOPE ESTIMATE = 0.036 SLOPE ESTIMATE = 0.026

  25. EVOLUTION OF TEMPERATURES SOKODE TMin SOKODE TMAX P-VALUE = 0 P-VALUE = 0 SLOPE ESTIMATE = 0.041 SLOPE ESTIMATE = 0.073

  26. EVOLUTION OF TEMPERATURES KARA TMin KARA TMAX P-VALUE = 0.01 P-VALUE = 0.081 SLOPE ESTIMATE = 0.036 SLOPE ESTIMATE = 0.038

  27. EVOLUTION OF TEMPERATURES MANGO TMin MANGO TMAX P-VALUE = 0.003 P-VALUE = 0 SLOPE ESTIMATE = 0.023 SLOPE ESTIMATE = 0.072

  28. SUMMARY OF CLIMATE TRENDS IN TOGO

  29. SUMMARY OF CLIMATE TRENDS IN TOGO • For precipitation, we note that Atakpame station provides a rainfall trend upward. Lomé, Sokodé, Kara and Mango have a rainfall trend downward. It should be noted that Sokodé has a net decrease. • For temperatures, we note that the trend is clearly increasing.

  30. CONCLUSION RClimDex is an excellent timely tool who facilitates our work.

  31. FIN DE LA PRESENTATION THANK YOU FOR YOUR KIND ATTENTION

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