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Adjustment of Global Gridded Precipitation for Orographic Effects Jennifer C. Adam 1 Elizabeth A. Clark 1 Dennis P. Lettenmaier 1 Eric F. Wood 2 1.Dept.

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Presentation on theme: "Adjustment of Global Gridded Precipitation for Orographic Effects Jennifer C. Adam 1 Elizabeth A. Clark 1 Dennis P. Lettenmaier 1 Eric F. Wood 2 1.Dept."— Presentation transcript:

1 Adjustment of Global Gridded Precipitation for Orographic Effects Jennifer C. Adam 1 Elizabeth A. Clark 1 Dennis P. Lettenmaier 1 Eric F. Wood 2 1.Dept. of Civil and Environmental Eng., University of Washington 2.Dept. of Civil Eng., Princeton University

2 Motivation: The Orographic Effect on Precipitation Figure taken from http://jamaica.u.arizona.edu increased condensation and precipitation due to orographic lifting decreased precipitation: the “rain shadow” precipitation divide * No global gridded precipitation datasets take into account the effects of orographic lifting

3 PRISM (Daly et al. 1994, 2001, 2002) (Parameter-elevation Regressions on Independent Slopes Model) 2.5 minute Topographic facets Regresses P against elevation on each facet 0 100 200 300 400 500 mm/month

4 Basin Area/Station Location Distributions 0.5 1.0 1.5 2.0 2.5 100% Cumulative Percent Africa Asia Australia Europe North America South America Station Count Basin Area 20% 100% 20% 100% 20% 100% 20% 100% 20% 100% 20% Elevation, km

5 From Nijssen et al. 2001 (J. Clim.) 400 800 1200 1600 Precipitation, mm/year 15,000 10,000 5,000 0 m 3 /s J F M A M J J A S O N D Observed with GPCC precipitation with PRISM precipitation Stream Flow Simulations 2°×2° GPCC1/8°×1/8° PRISM2°×2° PRISM

6 Objectives Consistent framework to account for orographic effects in 0.5° gridded gauge- based precipitation estimates on a global scale Utilize existing gridded precipitation product: Willmott & Matsuura (2001) with correction for precipitation under-catch by Adam & Lettenmaier (2003). Mean annual correction for 1979-1999

7 1.Definition of Correction Domain (regions of complex topography, only) 2.Average Correction Ratio for Gauged Basins: the “Budyko Method” 3.Fine-Scale Spatial Distribution of Correction Ratios within Gauged Basins 4.Fine-Scale Interpolation of Correction Ratios to Un-Gauged Basins then aggregate to 0.5° Outline of Steps Step 1 Step 2 Step 3 Step 4

8 Select Correction Domain 1.Pre-selection according to slope: - slopes calculated from 5-minute DEM - aggregated to half-degree 2. Set Slope Threshold -6 m/km (the approximate slope above which Willmott & Matsuura (2001) differs by more than 10% from PRISM) 3. Final Domain – smoothing then final selection Step 1

9 Slope, m/km 0 5 10 15 20 25 30 35 40

10 Basin-Average Correction Ratios: the “Budyko Method” 1. Determine “actual” basin average precipitation by solving 2 simultaneous equations: (1) Water Balance equation: (2) Derivative of Budyko (1974) E/P vs. PET/P curve 2. Calculate average correction ratio for each basin: Step 2

11 Energy Limited Moisture Limited S&V: Sankarasubrumanian and Vogel (2002) Uses an additional parameter: soil moisture storage capacity Budyko (1974) Curve

12 Gauged Basins 357 mountainous basins chosen

13 Spatial Distribution of Correction Ratios Within Gauged Basins 1.Break correction domain into a 5-min grid of “correction bands” – gives degree of topographic influence 2.Spatially distribute: use quadratic equation B, C: from constraints, i.e. (R ave conserved over basin and r band unity outside correction domain) A: from regressing R ave with PRISM (developed using 101 basins in western North America, tested over 5 basins in central Asia) Step 3

14 e.g. San Joaquin, CA Elevation, m Correction Ratio 123456 Correction Bands

15 Interpolate to Un-Gauged Areas 1.Interpolation at 5-min resolution: uses a linear distance weighting scheme Only interpolates to cells with the same correction band and the same slope type (i.e. windward vs. leeward – determined from NCEP/NCAR reanalysis data) 2. Aggregate 5-min correction ratios to the final resolution – 0.5° 3. Apply to original data via multiplication Step 4

16 0.4 0.8 1.2 1.6 2.0 Correction Ratio Results

17 ContinentCorr. DomainAll Areas Global20.2 %6.2 % Africa7.4 %1.4 % Eurasia20.3 %10.0 % North America34.4 %9.7 % South America26.6 %3.6% Increases by Continent

18 Summary Satisfies a need for gridded precipitation data that account for orographic effects in a globally-consistent framework Uses combination of water balance and Budyko (1974) curve to get magnitude, PRISM used to help derive spatial variability Final product: 1979-1999 0.5° climatology that accounts for gauge under-catch and orographic effects (global increases are 11.7% and 6.2%, respectively, for a net of 17.9%)

19 0 1 2 3 4 5 6 km 100% Percent Increase Africa Australia Eurasia North America South America Globe Increases with Elevation

20 Percent Increase Implied PRISM Adjustments (as compared to Willmott&Matsuura 2001) Net: 13.6%, 35.5% C v = 1.41 Adam et al. Adjustments Net: 16.1%, 41.6% C v = 0.42

21 Adam et al.PRISM Further PRISM Comparisons

22 Correction Bands 1 2 3 4 5 6 Least Topographic Influence Most Topographic Influence

23 Dominant Effective Wind Direction

24 Upslope Downslope Cross-Wind Slope Type

25 Where = Aridity Index Where = Soil Moisture Storage Index = Soil Moisture Storage Capacity Equations 1 2

26 Water Balance In General: Long term mean over watershed: “Q” obtained from streamflow measurements

27 0 0.5 1.0 1.5 2.0 2.5 km 20% 50% 20% Percent per Elevation Increment Africa Asia Australia Europe North America South America Distributions with Elevation Station Density Area


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