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CPC Drought Forecasting and NIDIS

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  1. CPC Drought Forecasting and NIDIS Douglas Le Comte NOAA/CPC 5th U.S. Drought Monitor Forum Portland, Oregon October 10-11, 2007

  2. Outline • Overview of how the CPC Outlook is put together • Recent changes to the Drought Outlook • Verification: How are we doing? • The Future: Meeting the Needs of NIDIS

  3. http://www.cpc.ncep.noaa.gov/products/expert_assessment/seasonal_drought.htmlhttp://www.cpc.ncep.noaa.gov/products/expert_assessment/seasonal_drought.html Latest Seasonal Drought Outlook

  4. Short and Long-term Forecast Contributions + +

  5. Principal Drought Outlook Inputs 2-Wk Soil Moisture CPC Long-Lead Precip. Outlook Constructed Analogue Soil Model Palmer 4-mo Probabilities Medium-Range Fcst

  6. Recent Changes • Began twice/month schedule (1st and 3rd Thursday) • Expanding CPC authors • Changed wording of headings (“Tendency”, valid dates)

  7. Changes Recently Considered • Add separate category for drought intensification • Abolish or re-define “Some Improvement” category • Automate verification calculations

  8. Drought Verification Jul-Sep 2007

  9. Improvement over PersistencePercent of Grid Points Correct vs a Forecast Based on Persisting Droughts Long-term mean = 13%

  10. NIDIS and Drought ForecastingFrom the NIDIS Implementation Plan, June 2007 • “Ensemble drought prediction is needed to maximize forecast skill, and downscaling is needed to bring coarse resolution drought forecasts from General Circulation Models down to the resolution of a watershed.” • “Improved understanding of the dynamical causes of long-term trends….” • Two basic approaches to drought prediction: 1) prediction of drought indices, and 2) prediction of hydrological conditions.

  11. FY08 Climate Test Bed Priority for NIDIS-Drought • New Drought Monitoring Products: Multi-model ensemble NLDAS • New Drought Forecast Tools: • Objective drought forecasts based on CFS and statistical tools • Improved seasonal forecasts based on improved land-atmosphere coupling • Improved medium-range prediction based on NAEFs

  12. Princeton Soil Moisture Forecast Ensemble Streamflow Prediction Coupled Forecast System

  13. http://www.hydro.washington.edu/forecast/monitor/outlook/index.shtmlhttp://www.hydro.washington.edu/forecast/monitor/outlook/index.shtml University of Washington Forecasts

  14. Two Path Approach to Improving Drought Forecasts at CPC • Continue to produce and refine seasonal drought outlooks for the general public • Develop objective seasonal probability forecasts for drought (guidance useful for an array of users)

  15. One Prototype Suggestion of a Probabilistic Forecast

  16. “Prediction is very difficult, especially about the future”Niels Bohr, Danish physicist (not Yogi Berra)