1. Adjustment of Global Gridded Precipitation for Orographic Effects Jennifer Adam

2. Outline 1.Background 2.Approach 3.Application over North America

3. Global Gridded Precipitation Spatial Interpolation of Gauge Measurements over Land Areas

4. The Orographic Effect on Precipitation

5. Interpolation from Valley Gauges *

6. PRISM (Parameter-elevation Regressions on Independent Slopes Model) 2.5 minute Topographic facets Regresses P against elevation on each facet

7. Approach

8. 1.Select Correction Domain and “Slope Bands” 2.Select Set of Basins that overlap with Correction Domain (must be gauged) 3.Determine “Actual” Basin Average Precipitation using Sankarasubramanian (2002) 4.Determine Scaling Ratios for each “Slope Band” 5.Apply the Scaling Ratios to an Existing Gridded Precipitation Dataset Outline of Steps

9. Select Correction Domain 1.Identified according to slope: - slopes calculated from 5-minute DEM - aggregated to half-degree 2. Set Slope Threshold -6 m/km (somewhat arbitrary) 3. Break Correction Domain into Slope Bands - six bands in correction domain

10. Slope

11. > 6m/km > 12m/km > 18m/km > 24m/km > 30m/km > 36m/km Correction Domain

12. 1.Select Correction Domain and “Slope Bands” 2.Select Set of Basins that overlap with Correction Domain (must be gauged) 3.Determine “Actual” Basin Average Precipitation using Sankarasubramanian (2002) 4.Determine Scaling Ratios for each “Slope Band” 5.Apply the Scaling Ratios to an Existing Gridded Precipitation Dataset Outline of Steps

13. World Streamflow Gauge Stations

14. 1.Select Correction Domain and “Slope Bands” 2.Select Set of Basins that overlap with Correction Domain (must be gauged) 3.Determine “Actual” Basin Average Precipitation using Sankarasubramanian (2002) 4.Determine Scaling Ratios for each “Slope Band” 5.Apply the Scaling Ratios to an Existing Gridded Precipitation Dataset Outline of Steps

15. “In mountainous areas, the best precipitation maps are derived by distributing streamflow back on the watershed and correcting for evapotranspiration.” -Harry W. Anderson

16. Water Balance In General: Long term mean over watershed: “Q” obtained from streamflow measurements Problem: how to estimate “E”

17. 1.Use VIC Model to Estimate “E” -relies on good precipitation estimates -relies on empirical parameters 2. Relate “E” to Potential Evapotranspiration (PET) - no need to rely on precipitation Alternatives for Estimating Evapotranspiration

18. Budyko (1974) Curve Energy Limited Moisture Limited

19. Budyko (1974) Curve Energy Limited Moisture Limited

20. 1.Semi-empirical relationship 2.Independent of energy and water balance equations. 3.Mean discrepancy between the E/P ratio calculated from curves and that derived by water balance amounts to 10% (Budyko and Zubenok, 1961). 4.Applies to river basins of “considerable” size – runoff dictated by climatic factors 5.Are other variables important? Discussion of Budyko Curve

21. 1.Milly (1994): - soil plant-available water holding capacity, various seasonality parameters 2.Zhang et al. (2001): -plant-available water coefficient, w (2.0 for forests, 0.5 for pasture and up to 1.0 for mixed vegetation) 3.Sankarasubrumanian and Vogel (2002): - soil moisture storage capacity Improvements to Budyko Curve

22. Sankarasubramanian et al. (2002) Curves

23. Obtaining Precipitation Where= Aridity Index Where= Soil Moisture Storage Index = Soil Moisture Storage Capacity

24. Estimating PET Temperature/Radiation-Based Methods: 1. Priestley-Taylor Method 2. Hargreaves Method -Solar Radiation determined from: a. VIC output b. latitude, julian day, solar declination Combination Method (Penman): - VIC output

25. Annual PET (1999) (Hargreaves Method)

26. Dunne & Willmott (1996) Soil Moisture Capacity

27. 1.Select Correction Domain and “Slope Bands” 2.Select Set of Basins that overlap with Correction Domain (must be gauged) 3.Determine “Actual” Basin Average Precipitation using Sankarasubramanian (2002) 4.Determine Scaling Ratios for each “Slope Band” 5.Apply the Scaling Ratios to an Existing Gridded Precipitation Dataset Outline of Steps

28. For Each Basin: averaged over the same period of years (as determined by the stream flow records) Calculate Average Scaling Ratios

29. Slope Bands in Basin 0 1 2 3 4 5 6

30. Create Scaling Ratios for each Slope Band (for each basin) Calculate Basin Average Scaling Ratio: Constraint: Solution: Problem Set-Up:

31. Example for a Single Basin By Definition May Not Be Valid! Also Works if R ave < 1

32. 1.Separate Basins into Regions that are Climatologically/Hydrologically Similar 2.For each Slope Band (1 through 6), find an average scaling ratio for each region by weighting the scaling ratios for the basins within that region: Weighting of Scaling Ratios Number of Valid Slope Bands Number of Cells within a Slope Band

33. 1.Select Correction Domain and “Slope Bands” 2.Select Set of Basins that overlap with Correction Domain (must be gauged) 3.Determine “Actual” Basin Average Precipitation using Sankarasubramanian (2002) 4.Determine Scaling Ratios for each “Slope Band” 5.Apply the Scaling Ratios to an Existing Gridded Precipitation Dataset Outline of Steps

34. Application over North America 1.Break the Continent into “Correction Regions” 2.Choose Streamflow Stations 3.Calculate Precipitation Scaling Ratios 4.Apply to Gridded Precipitation

35. Correction Regions 5 6 1 2 7 8 10 4 3 11 12 13 14 9 1.Climate Classification 2.Basin Boundaries 3.Location of Streamflow Gauges

36. Koppen Climate Classification

37. Hydro1k Basin Levels Level I Level III Level II Level IV

38. 1.Years of Operation 2.Drainage Area 3.Location 4.Nesting 5.Degree of Management Gauge Station Selection Criteria

39. Porcupine River Liard River S. Sasketchewan River Arkansas River Missouri River Santiago River

40. Rave 0 1 2 3 4 5 6

55. Final Thoughts 1.First application of this kind on a global scale 2.Problems will arise in regions where there are few or no streamflow gauge stations (Himalayas). 3.Sensitivity to delineation of “Correction Regions” 4.Much fine-tuning left to be done!