1. Methodology to integrate dynamical and statistical weather forecasts

2. Results are shown for nine different sub-basins of the Ebro River.
1. INTRODUCTION
The aim of this methodology is to produce probabilistic forecasts of accumulated rainfall for a forecast horizon of 15 days.
Results are shown for nine different sub-basins of the Ebro River.
Aragón
Ara
Cinca
Esera
Gállego
Muga
Noguera
Segre
Ter

3. 1. INTRODUCTION
Probabilistic forecasting : for each problem day and for each one of the forecasting horizons amounts of precipitation corresponding to different probabilities of occurrence are provided.
The forecasting system produces precipitation fields associated to probabilities of 5, 10, 25, 50, 75, 90 and 95% of being exceded (0.05, 0.1, 0.25, 0.5, 0.75, 0.9 and 0.95 quantiles)

4. 2. DATA
2.1 OBSERVED DATA
612 precipitation gauges located along the nine sub-basins.

5. 2. DATA
2.1 OBSERVED DATA
Spatial aggregation of the data belonging to each sub-basin for considering the whole precipitation that falls in the sub-basin each day.
For the Aragón basin, provided precipitation gauges (blue points) and areas of influence of each gauge inside the basin, calculated with Voronoi polygons.

6. 2. DATA 2.2 ECMWF: PROBABILISTIC FORECASTS ECMWF forecasts:
1 . Deterministic
2. Ensembles: 50 runs + control run

7. 2. DATA 2.2 ECMWF: REANALYSIS
Reanalysis: historical database of the meteorological fields that describe the atmosphere.

8. Statistical downscaling with two steps based in analogues.
3. METHODOLOGY
Statistical downscaling with two steps based in analogues.

9. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING

10. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING
SECOND DAY: SECOND DAY & FIRST DAY

11. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING
SECOND DAY: SECOND DAY & FIRST DAY
DOWNSCALING

12. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING
SECOND DAY: SECOND DAY & FIRST DAY
DOWNSCALING
3rd DAY: 3rd DAY & 2nd DAY & 1st DAY

13. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING
SECOND DAY: SECOND DAY & FIRST DAY
DOWNSCALING
3rd DAY: 3rd DAY & 2nd DAY & 1st DAY
DOWNSCALING

14. Probabilistic Forecast of ACCUMULATED Precipitation.
3. METHODOLOGY
Probabilistic Forecast of ACCUMULATED Precipitation.
FIRST DAY
DOWNSCALING
SECOND DAY: SECOND DAY & FIRST DAY
DOWNSCALING
3rd DAY: 3rd DAY & 2nd DAY & 1st DAY
DOWNSCALING
FIFTEENTH DAY

15. 4. RESULTS
RELIABILITY
Aragón sub-basin

16. 4. RESULTS
RELIABILITY
Aragón sub-basin

17. 4. RESULTS
RELIABILITY
Cinca sub-basin

18. 4. RESULTS
RELIABILITY
Noguera sub-basin

19. Ranked Probability Score
4. RESULTS
Ranked Probability Score

20. Ranked Probability Score
4. RESULTS
Ranked Probability Score

21. Ranked Probability Score
4. RESULTS
Ranked Probability Score

22. Ranked Probability Score
4. RESULTS
Ranked Probability Score

23. 4. RESULTS
RPS: Conclusions
RPS for all forecasts get worse as the forecast horizon advances (except for Climatology, which remains the same)
Persistence is always the worst forecast.
Our Analogue forecast improves the raw ECMWF prediction, both the control run and the Ensembles system.

24. 5. ECMWF’S CONGRESS, UEF2017
Preliminary results were presented in the “Using ECMWF’s Forecasts” international congress (UEF 2017, Central Headquarters of the ECMWF in Reading, UK, June 2017)
The presented results were evaluated only for some precipitation stations of Cataluña.

25. 5. ECMWF’S CONGRESS, UEF2017
RPS for the forecasting of a temporal horizon of 1 day.

26. 5. ECMWF’S CONGRESS, UEF2017
AUC for occurrence of extreme precipitations for every precipitation stations for 1 day forecast (extreme precipitation is defined as the 99th percentile).

27. 5. ECMWF’S CONGRESS, UEF2017 MAIN CONCLUSIONS
ECMWF Ensembles underestimate dry days and extreme rainfall at local scale.
Some post-process is required for downscaling EPS.
Analog/transfer statistical downscaling method improves:
Spread of the probabilistic forecast (Ranking Histogram).
General forecast of four classes (RPS/RPSS).
Extreme point rainfall forecast (ROC/AUC).
Limitations:
The used method requires long observed time-series (>5years).

28. 5. ECMWF’S CONGRESS, UEF2017

29. IMDROFLOOD – Kick off Meeting, 19-20 September 2016
Example
2016/07/22 10:30 UTC
OBSERVATION

30. IMDROFLOOD – Kick off Meeting, 19-20 September 2016
Example
2016/07/22 10:40 UTC
FORECAST

31. IMDROFLOOD – Kick off Meeting, 19-20 September 2016
Example
2.- Estimation of rain rate combining radar reflectivity and surface observations:

32. Resultados Avances en la estimación de lluvia desde radar
IMDROFLOOD – 10 de Mayo 2017
Resultados
Avances en la estimación de lluvia desde radar
Todos los falsos ecos
Falsos ecos más frecuentes

33. Resultados Pluviómetro finca 37°45'36.01" N 0°54'28.08" O
IMDROFLOOD – 10 de Mayo 2017
Resultados
Pluviómetro finca
37°45'36.01" N 0°54'28.08" O

34. Methodology to integrate dynamical and statistical weather forecasts
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