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Making Decisions for the Next Season Ian Foster Miles Dracup WA Dept of Agriculture Water Corporation Examples of Agricultural Forecasting Applications.

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Presentation on theme: "Making Decisions for the Next Season Ian Foster Miles Dracup WA Dept of Agriculture Water Corporation Examples of Agricultural Forecasting Applications."— Presentation transcript:

1 Making Decisions for the Next Season Ian Foster Miles Dracup WA Dept of Agriculture Water Corporation Examples of Agricultural Forecasting Applications Is there skill beyond climatology?

2 Climate Risk Management The importance of climate risk management to many sectors is a given Seasonal forecasts potentially have a major role BUT (for example): 95% of farmers find seasonal forecasts ‘interesting’ 25% of farmers find seasonal forecasts ‘useful’ Weeks (2005) Liebe Group Workshop, Wubin

3 The Nature of Decisions - A schedule of decisions Strategic vs Tactical decisions Negotiability of decisions (some may be locked in anyway) Capacity to respond to a forecast Information needs vary (eg, timeliness, means of delivery)

4 Season Types - Eastern Wheatbelt Condensed from 11 MUDAS season types (R Kingwell, DAWA) Proportion of long-term profit ‘Extra’ from climate knowledge

5 Changes in Season Types - Merredin

6 Schedule of Cropping Decisions

7 A Targetted Forecast A forecast that was aimed at strategic agricultural decisions in WA would look like: Long-lead (6 months) Likelihood of seasonal extremes (eg Tercile 1 vs Tercile 3) Available in summer/autumn Is communicated well Are we dreaming?

8 Current Seasonal Outlooks Operational outlooks –0-1 month lead-time –Driven by ENSO –Autumn ‘predictability barrier’ –Statistical (issues of stationarity wrt climate trends) –Expressed as probabilities Experimental outlooks –To 6 months lead-time –Rely on ENSO as a driver for seasonal memory –Autumn ‘predictability barrier’ –Potential to adapt to climate trends –Expressed as probabilities

9 Analysis of Risk - Methods Historical climate data (BoM, DAWA, farmers’ own records) Historical production data Analysis tools (Rainman, Climate Calculator …) Soil moisture (PYCAL, DAWA, APSIM) Crop Yield Estimates (STIN, APSIM, PYCAL …) Combine season-to-date conditions with climatology and derived products Used more for tactical decisions within-season Need facilitated access (eg develop partnerships for delivery)

10 Analysis of Risk - Rainfall Observed to dateFuture

11 Analysis of Risk - Crop Yields Source: Horses for Courses Bulletin Aug 2005. Site at West Morawa. Based on actual rain to 27 July 05, and historical finishes to the season.

12 The Search for Predictability - 1 Correlation of May-Oct rain with SOI indices over Feb-Apr. EPI derived in Nov of previous year Source: Telcik (2005)

13 The Search for Predictability - 2 Correlation of May-Oct rain with SOI indices over Mar-May. EPI derived in Nov of previous year Source: Telcik (2005)

14 Correlations with SSTs Correlation of MJJ rain with MJJ de- trended SST Source: Telcik (2005) Correlation of MJJ rain with JFM de- trended SST Location at 32.5 S 177 E

15 SST Anomalies in Neutral Years Source: Telcik (2005) Dry Av Wet May-Jul rainfall

16 Summary Climate risk management is important to many sectors. Seasonal climate forecasts form a part this. Current seasonal climate outlooks are not well matched to strategic decision making needs. Use of current conditions, climatology and derived products has practical application to tactical decisions. The search for predictability continues via enhancements to ENSO-based approaches and phenomena especially relevant to WA.


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