CPC’s U.S. Seasonal Drought Outlook & Future Plans April 20, 2010 Brad Pugh, CPC

(High-Res Soil Models) + (Seasonal Forecasts of Temperature and Precipitation) = (Soil Moisture/Drought Forecasts)

Using Soil Moisture Models to Monitor Drought at the NOAA Climate Prediction Center “Leaky Bucket” model: a 1-layer hydrological model. Uses observed precip. and temps to calculate soil moisture for a soil column of 1.6 meters. NLDAS 1-m and 2-m soil column; 4 separate models and ensemble; versions produced by NOAA EMC and the University of Washington / How is the percentile computed? Historical record? US:early 1930s - present Global: degree resolution

The NLDAS uses four land surface models: Noah, Mosaic, SAC and VIC, run in near real-time at the NCEP’s Environmental Modeling Center to support the National Integrated Drought Information System (NIDIS) and US Drought Monitor. North American Land Data Assimilation System (NLDAS North American Land Data Assimilation System (NLDAS) NLDAS NOAA/NCEPNASA/GSFC NOAA/OHD Princeton and Univ. of Washington Sponsored by the Climate Prediction Program of the Americas (CPPA) Office of Hydrologic Development (OHD) Noah- Mosaic-NASA SAC-Sacremento VIC-Univ of Washington

What Goes Into the Models? Hourly input: gauge precipitation, air temperature, air specific humidity, wind speed, etc. Water Fluxes Energy Fluxes State Variables: soil moisture, soil temperature, skin temperature, snow cover, snow water equivalent, snow depth “Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring….” Brian Cosgrove, NASA GSFC

Using the NLDAS Ensemble Mean Soil Moisture as a Drought Indicator Ensemble Mean NCEP Noah NASA Mosaic OHD SAC Princeton VIC Shallow layers of soil moisture can be used as agricultural drought indicators. Model runoff as hydro indicators. Percentile soil moisture levels correspond to U.S. Drought Monitor levels D0 to D4

CPC U.S. Drought Outlook: Short and Long-Term Forecast Contributions

Constructed Analogue Soil Model Medium-Range Fcst Palmer 4-mo Probabilities CPC Long-Lead Precip. Outlook Selected Drought Outlook Inputs

Challenges Blending short-term forecasts with seasonal forecasts Improving skill of forecasts at all time ranges Providing useful information for both the agricultural and hydrologic community Next step –develop an objective & probabilistic outlook

Next Step in Drought Forecasting A seasonal forecast of drought probabilities Consideration of agriculture and hydrology (short-term and long-term drought) Inclusion of short-term forecasts Potential of 1-Month Outlook (ag related) and Expansion to include Canada/Mexico

Two-Path Approach to Improving Drought Forecasts Continue to improve current seasonal forecasts Develop probabilistic seasonal forecasts for agriculture and water supplies Develop probabilistic seasonal forecasts for agriculture and water supplies Quantitative forecasts bring improvement

Future Expansion of NLDAS to Canada & Mexico May be extended to northern Mexico Funding/Resource Availability?

Improved Drought Forecasting and Early Warning NLDAS land models can be linked to downscaled seasonal forecast models to produce soil moisture and drought probability forecasts NOAA’s Climate Prediction Center is working with its partners to develop operational numerical drought forecast products. Forecast Soil Moisture Anomaly for April 2010 Issued March 2010 June

NWS River Forecast Centers: New Seasonal Streamflow Forecasts Candidate for a national hydrological forecast system

Proposed Suite of Probabilistic Seasonal Drought Forecasts Probability of Ag. Drought Probability of Hydro Drought Probability of Drought Total Column 2-m Soil Moisture Change Map Change in soil moisture percentiles Change Map Top 40 cm or root zone soil moisture Change in soil moisture percentiles Probability of Runoff or Streamflows Change Map Change in runoff or streamflow percentiles Total Drought Agricultural (Short-term) Drought Hydro (Long- term) Drought

Future Plans: Developing New and Innovative Forecast Products Develop next-generation drought forecast tools that provide probabilistic information on seasonal time scales Work with our partners in academia and the government to develop prototype products Potential expansion to a North American domain