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 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… 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… 4) Determine which practice is optimally profitable for that forecast condition, assuming certain price and cost conditions… Net Profit Distribution (Best Forecast Practice) 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 ) … 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… Define a second set of analog years, that include the entire historical record (e.g ) … 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… Profit Distribution (Best No-Forecast Practice) Profit Distribution (Best No-Forecast Practice) P($) $ $

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

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

NDJFM Panhandle Precipitation Dry (< 66 mm) Dry (< 66 mm) Normal Wet (> 96 mm) Wet (> 96 mm) Cold (< -0.5 C˚) Cold (< -0.5 C˚) Warm (> 0.5 C˚) Warm (> 0.5 C˚) Neutral MJJ Niño-3 SSTA MJJ Niño-3 SSTA May-June-July (MJJ) Niño-3 SSTA Phase vs. November-March (NDJFM) Panhandle Precipitation Tercile (85 Years: ) May-June-July (MJJ) Niño-3 SSTA Phase vs. November-March (NDJFM) Panhandle Precipitation Tercile (85 Years: ) Total

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

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

Q: Why Tactical Forecast Value ? 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 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, Zimbabwe (1997): Patt, A.G. et al., 2007: Learning from 10 Years of Climate Outlook Forums in Africa, Science, 318, A: To provide a probabilistic ‘Track Record’ of the consequences of using forecast information in a single year. A: To provide a probabilistic ‘Track Record’ of the consequences of using forecast information in a single year.

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… 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 ( ) at 3 farm sites using USHCN daily weather records. DSSAT winter wheat model + grazing subroutine (J. Zhang) 85 years of simulation ( ) at 3 farm sites using USHCN daily weather records.

Methods: Management Options 5 planting dates: Aug. 24, Sep. 8, Sep. 23, Oct. 8, Oct 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). 5 planting dates: Aug. 24, Sep. 8, Sep. 23, Oct. 8, Oct 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).

| | | | | | | | | | | | Aug. Sep. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Jun. Jul. | | | | | | | | | | | | Aug. Sep. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Jun. Jul. 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

Analog Years: NIN-3 Phase Forecasts ‘Forecast’ Dry, Normal, & Wet Years Observed NDJFM Panhandle Precipitation Observed NDJFM Panhandle Precipitation Dry (< 66 mm) Dry (< 66 mm) Normal Wet (> 96 mm) Wet (> 96 mm) ‘Forecast Wet’ ‘Forecast Normal’ Analog Years Total Analog Years Analog Years ‘Forecast Dry ’ Predicted NDJFM Precipitation Via MJJ Niño-3 Predicted NDJFM Precipitation Via MJJ Niño-3

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

Price & Cost Conditions Wheat Prices $ 3.22 / bu – Historical ( ) Mean $7.00 / bu – Elevated Price (Sept. 2007) Wheat Prices $ 3.22 / bu – Historical ( ) 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 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. Production Costs Texas Coop Extension 2007 dryland wheat and cow-calf budget.

Four Production Scenarios 1.Historical Wheat Price – Leased Pasture 2.Historical Wheat Price – Own Cattle 3.Elevated Wheat Price – Leased Pasture 4.Elevated Wheat Price – Own Cattle 1.Historical Wheat Price – Leased Pasture 2.Historical Wheat Price – Own Cattle 3.Elevated Wheat Price – Leased Pasture 4.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) Best Management Practice By Forecast Condition Best Management Practice By Forecast Condition Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry

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) Best Management Practice By Forecast Condition Best Management Practice By Forecast Condition Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry

Q: Commodity Price Determines Forecast Value ? No-Forecast Profit ($/hectare) Planting Date Applied N Stocking Rate Forecast Value ($/hectare) Best Management Practice By Forecast Condition Best Management Practice By Forecast Condition Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry No-Forecast Profit ($/hectare) Forecast Value ($/hectare) Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry $ 3.22/ bu Wheat $0.75/ kg LWG $ 3.22/ bu Wheat $0.75/ kg LWG $ 7.00/ bu Wheat $0.75/ kg LWG $ 7.00/ bu Wheat $0.75/ kg LWG

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) Best Management Practice By Forecast Condition Best Management Practice By Forecast Condition Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry

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

General Conclusions Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Profit Effects of Forecast Information are Probabilistic. 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 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 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. 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 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 Wet Years Forecast Wet Years Perfect Normal Years Forecast Normal Years Perfect Normal Years Forecast Normal Years Perfect Dry Years Forecast Dry years Perfect Dry Years Forecast Dry years NDJFM Precipitation (mm)

Forecast Skill ~ Forecast Value? Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Perfect Wet Perfect Normal Perfect Dry Forecast Wet Forecast Normal Forecast Dry Forecast Value ( $3.22/bu, $2.42/kg LWG)