West-wide and East-wide Seasonal Hydrologic Prediction Systems PI (West): Dennis P. Lettenmaier (U. of Washington) PI (East): Eric F. Wood (Princeton University) Primary Contributors: Andy Wood (UW) Lifeng Luo (Princeton) Others: Nathalie Voisin (UW), Ted Bohn (UW), Ali Akanda (UW), George Thomas (UW), Justin Sheffield (Princeton) NOAA CPPA Principal Investigator’s Meeting Aug.14-16, 2006 Tucson, AZ

1)Science Questions and Objectives 2)Background on both forecasting systems 3)Applications areas - seasonal forecasting -- climate forecasts -- initial conditions estimates - shorter lead forecasting (15 day) - drought monitoring 4)External Interactions Topics

CPPA vision: improve operational intraseasonal to interannual climate prediction and hydrological applications. CPPA land-atmosphere interaction science objectives: (1)improve understanding and simulation of coupled land-atmosphere processes through observation, data analysis, and modeling studies; (2) determine the influence of land-atmosphere processes on intra-seasonal to interannual climate predictability; and (3) use this knowledge to advance operational forecasts, monitoring, and analysis. The two projects target the CPPA goal of improving the scientific basis for operational hydrologic forecasts through use of NOAA (and other) climate forecasts and data products. Governing CPPA Science Objectives

The west/east hydrologic forecast systems are founded on almost a decade of NOAA funded development  LDAS project  VIC development, implementation for LDAS region, and 50 year retrospective (Mitchell et al., 2004; Maurer et al., 2002)  OGP GCIP/GAPP  developed approaches for using NCEP seasonal climate model forecasts (Ohio River basin and East Coast)  CDEP/ARCS  extension of retrospective simulations to 1915; expansion of forecast activities to westwide domains; exploration of shorter lead forecasts NOAA OHD offered a letter of support for the current project NASA funding has also played a role (NSIPP/GMAO) Background

West-wide System

West Side (Washington) East Side (Princeton) East-wide System

Research Objectives 1)To understand the predictability of the hydrological cycle at medium range and seasonal-to-interannual timescales 2)To develop the seasonal / medium range hydrological prediction capability for the U.S. 3)To develop the real-time drought monitoring capability for the U.S. 4)Test and implement improved data assimilation methods for both in situ and remotely sensed data 5)Various applications related goals, e.g., link to reservoir system models for reservoir contents analysis Both Systems

Soil Moisture State Snowpack State Both Systems VIC

Streamflow Routing Network Both Systems 1/8 degree, Ohio R. basin

UW Forecast Approach Schematic NCDC COOP station obs. up to 3 months from current local scale (1/8 degree) weather inputs soil moisture snowpack VIC Hydrologic model spin up SNOTEL Update streamflow, soil moisture, snow water equivalent, runoff 25 th Day, Month years back index stn. real-time met. forcings for spin-up gap Hydrologic forecast simulation Month 12 INITIAL STATE Observed SWE Assimilation ensemble forecasts ESP traces CPC-based outlook NCEP CFS ensemble NSIPP-1 ensemble West-wide System

Seasonal Hydrological Prediction System LSM VIC Noah SAC Routing Multiple GCM Ensemble Forecast NLDAS (initial conditions) Bayesian Merging Weather “Generator” (resampling and scaling historical time series) 1/8 degree daily time step 1/8 degree Monthly time step Obs. Climatology Climate indices Teleconnection 1/8 degree GCM resolution and Coarser Large scale Bayesian Merging ESP VIC Noah SAC East-wide System

West-wide System forecast/westwide/

East-wide System

SWESoil MoistureRunoffPrecipTemp Apr-06 May-06 Jun-06 Both Systems Spatial Forecasts of Variable Fields

1)Science Questions and Objectives 2)Background on both forecasting systems 3)Operational applications research areas - seasonal forecasting -- climate forecasts -- initial conditions estimates - shorter lead forecasting (15 day) - drought monitoring 4)External Interactions Topics

Ensemble Streamflow Prediction (ESP) ICsSpin-upForecast observed recent met data to generate “perfect” ICs ensemble of historical met data to generate ensemble forecast hydrologic state Applications: climate forecast

CPC Seasonal Outlook Use Challenge: Seasonal (3-month) probabilities must be converted to daily meteorological values at the scale of the hydrology model Applications: climate forecast

Flow location maps give access to monthly hydrograph plots, and also to raw forecast data. Streamflow Forecast Details Clicking the stream flow forecast map also accesses current basin-averaged conditions Applications: streamflow

Bayesian Merging of Information Bayes Theorem Likelihood function (relates local scale to GCM scale and above) Prior (local climatology) Posterior 1/8 th degree scale variable Variable at GCM scale and above Applications: climate forecast

Climatological Forecast Streamflow: Forecast Applications: streamflow forecast

Realtime forecasts (Target month: ) Target Month Lead 2 months Soil is likely to be drier than normal Target Month Lead 1 month Soil will be drier than normal with more certainty Applications: soil moisture forecast

Drought Monitoring (Forecast Validation) Applications: soil moisture forecast

Realtime Drought Monitoring Princeton, 1/8 degree Long-term Historical Observed Atmos. Forcing Realtime Atmos. Forcing VIC Long-term Hydrological States VIC Realtime Hydrological States Drought-related Analysis and Nowcast NLDAS Realtime Atmos. Forcing VIC Realtime Hydrological States UW, ½ degree same method Applications: drought analysis / prediction

Real-time Daily Nowcast SM, SWE Applications: drought analysis / prediction

Realtime Drought Monitoring Applications: drought analysis / prediction

UW is implementing a 15- day global real-time hydrologic forecast Initially using T. Hamill’s “reforecast” datasets to allow bias-correction As procedures stabilize, 15-day forecasts will be incorporated into the US systems. Applications: 15-day forecasts

Monthly Avg Flow Bayesian Merging of Multi-LSM forecasts Testing in 3 basins (Salmon, Gunnison, Feather) - retrospective (simulation AND ensemble forecast modes) Applications: Multi-model forecasts

1)Science Questions and Objectives 2)Background on both forecasting systems 3)Applications areas - seasonal forecasting -- climate forecasts -- initial conditions estimates - shorter lead forecasting (15 day) - drought monitoring 4)External Interactions Topics

NOAA Applied Science Users with Real Needs West-wide Interactions

Snow water content on April 1 April to August runoff McLean, D.A., 1948 Western Snow Conf. SNOTEL Network Hydrologic prediction and the NRCS PNW West-wide Interactions

External Interactions UW Hydrologic Forecast and Nowcast Systems U. Arizona / USBR forecast study, Lower Colorado basin NWS Hydrologic Ensemble Prediction Experiment 3TIER Environmental Forecast Group NRCS National Water and Climate Center NOAA Climate Prediction Center’s US Drought Outlook Miscellaneous: Seattle City Light, energy traders, hydropower utilities, NOAA regional climate offices UW Rick Palmer Group Puget Sound region flow forecasts UW Climate Impacts Group (CIG) Annual Water Outlook meetings NOAA National Centers for Environmental Prediction (NCEP) testbed activities Columbia River Inter-tribal Fish Commission Klamath R. Basin Bureau of Reclamation UCI / California Dept of Water Resources WA State Dept of Ecology & Yakima R. Basin Bureau of Reclamation new US Drought Monitor Princeton University Hydrologic Forecast System West-wide Interactions

UW methods used in real-time CPC-based forecasts produced for a City of Seattle Water Utilities Consortium Interactions

NCEP EMC (Ken Mitchell, Youlong Xia, and others) West-wide and East-wide Interactions RUNOFF SWE NOAH undersimulated snow early runoff peak

Westwide System –  Finish streamflow forecasting implementation for Western half of US  Implement reservoir contents forecasts  Explore approaches for incorporating 15-day forecasts  Refine snow-related data assimilation Eastwide System -  Finish streamflow forecasting implementation for Eastern half of US  Expand inputs to Bayesian merging of climate forecasts Both -  Continue testing and transfer of various elements to NCEP EMC  Resolve UW-Princeton method differences as two forecasting domains are knit together Future Plans

Thank you -- Questions?