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GEWEX Americas Prediction Project (GAPP). Jin Huang NOAA Office of Global Programs September 17, 2003 Boulder, CO. GAPP History. GAPP is a follow-on program to GCIP GAPP extends from Mississippi river basin to SW and NW US to cover GAPP advances its focus from analysis to prediction
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GEWEX Americas Prediction Project(GAPP) Jin Huang NOAA Office of Global Programs September 17, 2003 Boulder, CO
GAPP History • GAPP is a follow-on program to GCIP • GAPP extends from Mississippi river basin to SW and NW US to cover • GAPP advances its focus from analysis to prediction • GAPP Science Advisory Group (SAG) provides science guidance to both agencies. 1995-2001 2001-2007
GAPP Objectives • Improve monthly/seasonal climate prediction focused on improved understanding and modeling of land-atmosphere interactions. • Provide decision support through interpretation of climate forecasts for water resource management applications.
Observations Predicted: Without Soil Moisture Initialization 10 3. 1. 0.5 0.2 0 -0.2 -0.5 -1. -3. -10 1988 U.S. Drought Prediction Improved by Soil Moisture Initial Condition Predicted: With Soil Moisture Initialization (using full GLDAS system) JJA precipitation anomalies (in mm/day, after R. Koster)
GAPP Objectives • Improve monthly/seasonal climate prediction focused on improved understanding and modeling of land-atmosphere interactions. • Provide decision support through interpretation of climate forecasts for water resource management applications.
GAPP Supports BoR Decision Support System BoR AWARDS - ET Toolbox System GAPP Products
GAPP Major Research Activities Objective 1: Improve monthly/seasonal climate prediction focused on improved understanding and modeling of land-atmosphere interactions. • Improve understanding and modeling of land-surface processes • e.g. NAME, soil moisture, snow, vegetation, topography,… • Incorporate new understanding into climate prediction system (thru GAPP NOAA Core Project) • Land surface models • Land Data Assimilation System (LDAS) • Regional climate models • Provide hydrologic data sets (e.g. soil moisture) for climate model development/validation and predictionresearch • e.g. Regional reanalysis, long-term and realtime precipitation data; CEOP
Parameterization of Fractional Snow Cover Yang and Niu CLM2/Default – OBS CLM2/Yang – OBS The significantwarm biasboth in Eurasia and North America fromthe default NCAR Community Climate Model (CAM2/CLM2) is largelyreducedby using the Yang et al (1997) SCF scheme
GAPP Major Research Activities Objective 1: Improve monthly/seasonal climate prediction focused on improved understanding and modeling of land-atmosphere interactions. • Improve understanding and modeling of land-surface processes • e.g. NAME, soil moisture, snow, vegetation, topography,… • Incorporate new understanding into climate prediction system (thru GAPP NOAA Core Project) • Land model improvement • Land Data Assimilation System (LDAS) • Regional climate models • Provide hydrologic data sets (e.g. soil moisture) for climate model development/validation and predictionresearch • e.g. Regional reanalysis, long-term and realtime precipitation data; CEOP
NOAA GAPP Core Project……to provide a pathway for research to NOAA operations • NCEP • OHD • NESDIS
GAPP Major Research Activities Objective 1: Improve monthly/seasonal climate prediction focused on improved understanding and modeling of land-atmosphere interactions. • Improve understanding and modeling of land-surface processes • e.g. NAME, soil moisture, snow, vegetation, topography,… • Incorporate new understanding into climate prediction system (thru GAPP NOAA Core Project) • Land surface models • Land Data Assimilation System (LDAS) • Regional climate models • Provide hydrologic data sets (e.g. soil moisture) for climate model development/validation and predictionresearch • e.g. Regional reanalysis, long-term and realtime precipitation data; CEOP (Coordinated Enhanced Observation Period)
REGIONAL REANALYSIS (NCEP) (REGIONAL REANALYSIS DOMAIN) High Resolution, Dynamically Consistent Historical NA Analysis for: 1) Diagnostics Studies 2) Prediction Model Initialization and Validation. NCEP/ETA MODEL 32 KM Spatial Resolution; 3 Hourly Temporal Resolution; 1979 through 2002. A SYSTEM WILL BE IN PLACE TO CONTINUE PRODUCING THESE FIELDS BEYOND 2002 1-Year RR data (Feb. 95-Jan. 96) is available now at: http://www.emc.ncep.noaa.gov/mmb/rreanl/index.html
GAPP Major Research Activities (cont.) Objective 2 : Provide decision support through interpretation of climate forecasts for water resource management applications • Improve hydrologic prediction • Downscaling, biases correction of climate forecasts, initialization, • Ensemble streamflow prediction (ESP) • Hydrologic predictability • Model improvement • Develop water resources decision tools • Helping water managers to understand and use climate forecasts • Developing place based tools, tools for using ensemble climate forecasts • Assessing forecast quality for decision making
soil moisture signal dominant; • snow signal dominant in W in summer • climate signal strong in SE in winter Hydrologic Predictability Most of hydrological predictability comes from initial boundary conditions => importance of LDAS (Maurer and Lettenmaier)
GAPP Major Research Activities (cont.) Objective 2 : Provide decision support through interpretation of climate forecasts for water resource management applications • Improve hydrologic prediction • Downscaling, biases correction of climate forecasts, initialization, • Ensemble streamflow prediction (ESP) • Hydrologic predictability • Model improvement • Develop water resources decision tools • Helping water managers to understand and use climate forecasts • Developing place based tools, tools for using ensemble climate forecasts • Assessing forecast quality for decision making
Ensemble Predictions (Probabilistic Forecasts) Assess Value in Decision- Making Climate Prediction Assimilate Observations and Handle Input/Output Uncertainties GAPP Strategy for Water Resources Weather & Climate Inputs Hydrologic Model Water Resources Decision Tool Better Decisions
GAPP CCSP-GWC ISIP • Drought monitoring • Prediction products for water monitoring • Land surface processes and feedbacks • Regional climate models • Mountains, precipitation, • Water resources • Clouds/Radiation • Water vapor and energy balances • Aerosols and clouds • Water and carbon • Sea ice • Global models • SST Forcing • Teleconnections • Etc. GAPP’s Role in ISIP and GWC
Summary on GAPP • Land surface expertise • Water resource applications • Critical datasets • Mechanism for science/technology infusion to NOAA operations