The Value of ENSO Forecast Information To Dual

The Value of ENSO Forecast Information To Dual Purpose Winter Wheat Production In the U. S. Southern High Plains Steve Mauget USDA-ARS Plant Stress & Water Conservation Lab, Lubbock, TX John Zhang USDA-ARS Grazinglands Research Lab, El Reno, OK Jonghan Ko USDA-ARS Agricultural Systems Research Unit, Ft Collins, CO

Analog Years Method 1) Given set of analogous years in historical record marked by a certain forecast condition over a growing region… 2) For each analog year, conduct cropping simulations… 3) Repeat simulations for a range of management practices… 4) Determine which practice is optimally profitable for that forecast condition, assuming certain price and cost conditions… Net Profit Distribution (Best Forecast Practice) P($) $

Analog Years Method: Forecast Value • Define a second set of analog years, that include the entire historical record (e. g. 1915 -1999) … • Repeat process 1 -4 to define a best management practice for climatological (i. e. , ‘No Forecast’ ) conditions … • Form a distribution of profit outcomes for the forecast analog years, using the best No-Forecast practice… P($) Profit Distribution (Best No-Forecast Practice) $

Average Forecast Profit Effect <FV> = < $(Forecast)> Profit Distribution (Best Forecast) - <$(No-Forecast)> Profit Distribution (Best No-Forecast) Where, <$(Forecast)> = Average profit from best management practice for the specified forecast condition. <$(No-Forecast)> = Average profit from best management practice when no forecast information is available.

‘NIN-3’ ENSO Phase Forecast System Correlation of December-January-Februrary (DJF) Panhandle Rainfall with DJF SSTA Niño 3 Region

May-June-July (MJJ) Niño-3 SSTA Phase vs. November-March (NDJFM) Panhandle Precipitation Tercile (85 Years: 1915 -1999) NDJFM Panhandle Precipitation Dry Normal Wet (< 66 mm) (> 96 mm) MJJ Niño-3 SSTA Total Cold (< -0. 5 C˚) 10 3 1 14 Neutral 13 18 15 46 Warm (> 0. 5 C˚) 5 8 12 25 Total 28 29 28 85

Dual Purpose Winter Wheat Production | | | | Aug. Sep. Oct. Nov. Dec. Jan. Feb. Mar. Planting Dormant Period & Grazing | | Apr. | May | Jun. | Jul. Harvesting Heading & Grain Filling

Tactical vs. Strategic Forecast Value <FV> = < $(Forecast)> - <$(No-Forecast)> Profit Distribution (Best Forecast) Profit Distribution (Best No-Forecast) Forecast Value Distribution Min 33 rd % Median 66 th % Max

Q: Why Tactical Forecast Value ? A: To provide a probabilistic ‘Track Record’ of the consequences of using forecast information in a single year. Yakima River Valley (1977): Glantz, M. H. , 1982: Consequences and Responsibilities In Drought Forecasting: The Case of Yakima, 1977, Water Resourc. Res. , 18(1), 3 -13 Zimbabwe (1997): Patt, A. G. et al. , 2007: Learning from 10 Years of Climate Outlook Forums in Africa, Science, 318, 49 -50.

Q: Why Tactical Forecast Value ? A: Seasonal climate forecasts are probabilistic. The profit effects of forecast information are also probabilistic… There is risk associated with forecast use…

Methods: Dual Purpose Simulations • DSSAT winter wheat model + grazing subroutine (J. Zhang) • 85 years of simulation (1915 -1999) at 3 farm sites using USHCN daily weather records.

Methods: Management Options • 5 planting dates: Aug. 24, Sep. 8, Sep. 23, Oct. 8, Oct. 23. • 5 nitrogen (N) application rates: 30, 60, 90, 120, or 150 kg ha-1 applied at planting. • 5 stocking rates (SR): 0. 5, 1, 1. 5 or 2 head ha-1, or no grazing (SR=0. 0 head ha-1).

80 Dual Purpose: Grain + Grazing Profits 25 Grain Only: Grain Profits Only 20 Grazing Only: Live Weight Gain Profits Only 1 Fallowing Option: Net Profit = $0. 0 / ha | | | | Aug. Sep. Oct. Nov. Dec. Jan. Feb. Mar. | | Apr. | May | Jun. | Jul.

Analog Years: NIN-3 Phase Forecasts ‘Forecast’ Dry, Normal, & Wet Years Observed NDJFM Panhandle Precipitation Dry Normal Wet (< 66 mm) (> 96 mm) ‘Forecast Dry’ Predicted NDJFM Precipitation ‘Forecast Normal’ Via MJJ Niño-3 ‘Forecast Wet’ Total 10 3 1 14 Analog Years 13 18 15 46 Analog Years 5 8 12 25 Analog Years 28 29 28 85

Analog Years: Perfect Dry, Normal, & Wet Years Observed NDJFM Panhandle Precipitation Dry Normal Wet (< 66 mm) (> 96 mm) Total ‘Perfect Dry’ 28 0 0 28 Analog Years Predicted NDJFM ‘Perfect Normal’ Precipitation 0 29 Analog Years 0 0 28 28 Analog Years 28 29 28 85 ‘Perfect Wet’ Total

Price & Cost Conditions Wheat Prices $ 3. 22 / bu – Historical (1978 -2006) Mean $7. 00 / bu – Elevated Price (Sept. 2007) Live Weight Gain (LWG) Value $0. 75 / kg LWG - Leased Pasture Rental Rate $2. 42 / kg LWG – Wheat Producer Owns Cattle Production Costs Texas Coop Extension 2007 dryland wheat and cow-calf budget.

Four Production Scenarios 1. 2. 3. 4. Historical Wheat Price – Leased Pasture Historical Wheat Price – Own Cattle Elevated Wheat Price – Leased Pasture Elevated Wheat Price – Own Cattle

Historical Wheat Prices - Leased Pasture Conditions ($ 3. 22 /bu ) ($0. 75 / kg LWG) No-Forecast Profit ($/hectare) Planting Date Applied N Stocking Rate Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Best Management Practice By Forecast Condition

Elevated Wheat Prices – Leased Pasture Conditions ($ 7. 00 bu ) ($0. 75 / kg LWG) No-Forecast Profit ($/hectare) Planting Date Applied N Stocking Rate Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Best Management Practice By Forecast Condition

Q: Commodity Price Determines Forecast Value ? No-Forecast Profit ($/hectare) $ 3. 22/ bu Wheat $0. 75/ kg LWG Planting Date Applied N Stocking Rate Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Best Management Practice By Forecast Condition No-Forecast Profit ($/hectare) $ 7. 00/ bu Wheat $0. 75/ kg LWG Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry

A: Profit Margin Determines Forecast Value $ 7. 00/bu, $0. 75 / kg LWG & Production Costs * 2 No-Forecast Profit ($/hectare) Planting Date Applied N Stocking Rate Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Best Management Practice By Forecast Condition

Value of Best No-Forecast Practices (No-F V) No-F V = $(Best No-F Practice) - $(Reference Practice) Value of Best No-Forecast Practice Best Management Practice For No-Forecast Conditions Reference Practice

General Conclusions Profit Effects of Forecast Information are Probabilistic. Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Forecast information may not ‘Pay Off’ every year….

Summary Profit margins can influence forecast value effects Value of best no-forecast practices Improved regional forecast skill may not lead to increased tactical forecast value at the farm level See: Mauget, S. A. , Zhang, J. and Ko, J. , 2009: The value of ENSO forecast information to dual purpose winter wheat production in the U. S. Southern High Plains. Journal of Applied Meteorology and Climatology, October 2009.

Summary Similar analyses could be done in any area sensitive to climate-related risk… But while seasonal forecasts may re-define climate related risk they will never eliminate it… To ease adoption, provide a probabilistic ‘track record’ of how forecast information re-defines that risk.

Conclusion (cont. ) Mauget, S. A. , Zhang, J. and Ko, J. , 2009: The value of ENSO forecast information to dual purpose winter wheat production in the U. S. Southern High Plains. Journal of Applied Meteorology and Climatology, October 2009.

Farm Level NDJFM Precipitation By Analog Years Perfect Wet Years Forecast Wet Years Perfect Normal Years Forecast Normal Years Perfect Dry Years Forecast Dry years NDJFM Precipitation (mm)

Forecast Skill ~ Forecast Value? Forecast Value ( $3. 22/bu, $2. 42/kg LWG) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry