Daily rainfall time-series using wavelet and rs vegetation

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Yann Chemin

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Daily rainfall time-series using wavelet and rs vegetation

  1. 1. Daily rainfall time-series usingwavelet & RS vegetation Yann Chemin Water for a food-secure world
  2. 2. Contents Rational Methodology Implementation Hinkuregoda Exp Conclusions Water for a food-secure world
  3. 3. RationalFew Meteorological stationsDaily Rainfall pointsFrom point to GRIDWith Time-SeriesUse vegetation as driver Water for a food-secure world
  4. 4. Methodology Water for a food-secure world
  5. 5. Spatial Interpolationr.HP1&2 @ frequency slice Water for a food-secure world
  6. 6. Frequency data Red = r.HP1 Green = r.HP2 Blue = n.LP2 note the ½ and ¼ signal dimensions from 4018 Water for a food-secure world
  7. 7. Test Rainfall Reconstruction Is the algorithm working? Assess the spatial output Assess the time-series output Is the procedure loosing data? Cumulative rainfall consistency check Water for a food-secure world
  8. 8. Spatial & Temporal Output Water for a food-secure world
  9. 9. Cumulative Rainfall (11 years) Water for a food-secure world
  10. 10. Hinkuragoda Experiment Remove Hinkuragoda dataset (Mahaweli) Rerun processing Assess impact on reconstruction Assess histogram statistics changes Water for a food-secure world
  11. 11. Hinkuragoda Experiment Water for a food-secure world
  12. 12. Hinkuragoda Experiment Experiment Envt  Source rain gauges: 30-50 Km radius Experiment Results  Cumulative Rainfall: 85% accuracy  Reconstruction: Linear difference Water for a food-secure world
  13. 13. Difference Histograms Water for a food-secure world
  14. 14. Histograms statistics Exp1 * Exp2 * Exp1 Exp2  Histogram shapesSample size 627 618 4018 4018Minimum -106 -112  No changesMaximum 108 110Arithmetic mean 3.1 6.1 0.0 0.7Unbiased variance 121 132Biased skewness 0.6 0.9 0.6 1.6Biased kurtosis 4.4 3.1 21 21* Removed diff=0 Water for a food-secure world
  15. 15. On-Going Thoughts Working well with representative met.Stations Distance to Met Stations induces errors Errors for cumulative rainfall: linear Errors of rainfall event (1-3 days shift) Climate zoning Vs Heterogeneity Water for a food-secure world
  16. 16. Potential Applications Ungauged basins: − Improve sampling rate of hydrological modeling Regional climate modeling − RegCM (Solomon is using it):  Precip Evap. overestimation in Version 3  Precip forcing: EnKF assimilate Cevap to obs. Precip & Ev Food security early warning − Markov chains, EnKF etc to store momentum of variations − Higher S-T res than actual for FS forecasting models Agricultural insurance Water for a food-secure world
  17. 17. Thank you Water for a food-secure world

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