Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington NHPS briefing NWS/OHD Silver Spring, MD March 5, 2010.

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Presentation transcript:

Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington NHPS briefing NWS/OHD Silver Spring, MD March 5, 2010 University of Washington Hydrological Monitoring and Forecast Systems

Outline Overview University of Washington Hydrological Seasonal Forecast Systems – Field measurement-based forcings – Remote sensing assimilation Operational test bed for NOAA – Technological development and transfer – Nation-wide and International collaboration Research and Applications Future developments

Funding Scientific and Technological Development Users ProjectsFeedback Technological TransferScientific Development NOAA NASA Testbeds Technique development Resource application University of Washington Princeton University Scientific and non- scientific articles Courses and workshops Interistitutional collaboration Governmental Agencies Academic groups Stakeholders

Runoff Forecast Hydrological Monitoring and Forecast Drought Monitoring and Forecast Streamflow Forecast Field Observations Remote Sensing Ensemble TechniquesStatistical MethodsModeling Seasonal Forecasts

University of Washington/Princeton University North American Hydrological Systems (NAHS) Low resolution (1/2 degree) SWM High resolution (1/8 degree) WSHFS NAHS Forecasting Monitoring Forecast USMEX In progress (05/2010) done 1/8 NCAST ESP CPC CFS ½ NCAST Multi-model Drought ESP Drought CPC Drought Multi-model

The Group 3 people (2 at the UW and 1 at PU) Tasks – Operation 2 Hydrological Systems (hydrological and drought Monitoring and forecast) – Technological Development Implementation of new techniques for hydrological and drought forecast – Research Development of new techniques and investigation of hydrological and drought events – Technological Transfer Courses and/or workshops, meetings, and collaborations

University of Washington/Princeton University West-wide Seasonal Hydrological Forecast System (WSHFS) Sub-continental Mid-Resolution

The WSHFS-Operational Quasi-real-time representation of current Hydrological Conditions: NCAST – Currently covers all US, Mexico, and the upper Columbia basin in Canada Uses 7 nodes with 3 to 4 processors each (total of 27) and 1 massive storage raid system of 1.7Tb (access to a second with another Tb) NCAST downloads meteorological data from ACIS (NCDC-COOP stations) every morning at 8:15am Over 2000 stations are used by Index-station method to generate the forcings at 1/8 degree (>800 in Mexico and 10 in the Upper Columbia River Basin in Canada) Assimilates SNOTEL data (NCAST and Forecast) On a forecast mode produces weekly hydrological forecasts

University of WashingtonUniversity of Washington and Princeton University NCAST Evolution

WSHFS-Forecast mode (ESP) University of WashingtonUniversity of Washington and IMTA (Mexico)

WSHFS (current operations) ESPCPC

Applications and Research Climate Impacts Group – Quarterly Forecast for the PNW – Annual Forecast for users in the states of WA, OR, and ID Wildfire Forecast (UC Merced and USDA Forest Service) CLIMAS (University of Arizona and Mexican Institutions) Drought Predictability over Mexico using WSHFS and applying ESP and CFS techniques An average of 1.2 requests of data per month US and Mexican agencies and Institutes consult or are in process to use some of the tools (Instituto Mexicano de Tecnologia del Agua [IMTA], Comision Nacional del Agua [CNA])

Applications CLIMAS Wildfire Forecast Climate Impacts Group

Long-term Historical Observed Atmos. Forcing Realtime Atmos. Forcing VIC Long-term Hydrological States VIC Realtime Hydrological States Soil Moisture Percentiles (SMI) ESPs, CFSs, and Nowcast RMSE OBS (NCAST) and Forecast (ESP and CFS) Initializations Mar, May, Jul, Sep, Nov Mexico, North Central, Northwest, andSouth Modelling-based Atmos. Forcing + Long-term VIC CFS-Long-term Hydrological States ESPCFS NCAST RESEARCH Drought Predictability Assessment

Initial Conditions March April May June ObservationsForecasts ESPCFS Ensemble Performance (soil moisture Percentiles) 2007

Initialization month Forecast month 1-month lead 2-months lead RMSE forecast /RMSE climatology RMSE forecast Drought Predictability 1-month lead

Current and Future Developments ESP and CPC extension to the Eastern US SIMOP Implementation over the Yaqui River Basin Assimilations of MODIS-snow product Implement CFS over the US and Mexico

Simulator Optimization Tool (SIMOP)

Surface Water Monitor (SWM) Sub-continental Low-Resolution

Surface Water Monitor Drought Monitoring – Daily nowcast of Soil moisture and Runoff percentiles at ½ deg spatial resolution. – Multimodel based ensembles for the CONUS and Mexico Drought Prediction – Forecast of Soil Moisture (SM) and 3 months cumulative Runoff (RO) percentile at ½ deg spatial resolution out to 1 to 3 months.

Drought Monitoring (Daily Process Flow) Previous day’s meteorological observations from index stations, gridded to 0.5 degree All models use same input forcings, different formats Model results expressed as percentiles of historical output Average Percentiles Compute Percentiles Make Plots

Multimodel based SM percentile Nowcast ( ) ( Models used:  VIC  Noah 2.8  Sacramento/Snow-17 (SAC)  CLM 3.5 VIC NOAH_2.8 SAC CLM Multimodel

Forecasts based on: -Ensemble Streamflow Prediction (ESP) Climatological ( ) weather ensembles ENSO years only -Climate Prediction Center (CPC) weather forecasts Climatological weather ensembles adjusted by CPC predicted monthly anomalies. ( Work in progress ) Drought Prediction

Initial Hydrologic Conditions on Climatological ESP based 1 month lead SM percentile forecast CPC weather forecasts based 1 month lead SM percentile forecast ENSO subset ESP based 1 month lead SM percentile forecast

Initial Hydrologic Conditions on Climatological ESP based 3 month lead RO percentile forecast CPC weather forecasts based 3 month lead RO percentile forecast ENSO subset ESP based 3 month lead RO percentile forecast

Use of SWM in United States Drought Monitor SWM SM and RO percentile nowcast is used by USDM for drought monitoring y/drought_indicators/223/soil_moisture/278

Use of SWM in Drought Outlook SWM ESP based forecast is one of the tools consulted in the monthly drought monitor briefings to provide drought outlook ng/209/soil_moisture/338

Technological Transfers The system has been transferred to the UC Irvine and the Mexican Institute of Water Technology A transfer to the Pacific National Laboratory is in progress Two additional developments have been transferred to Mexican institutions