# Presentation: 118623

## An experimental real-time seasonal hydrologic forecast system for the western U.S. 

- Andrew W. Wood and
- Dennis P. Lettenmaier
- Department of  Civil and Environmental Engineering
- University of Washington
- Climate Diagnostics and Prediction Workshop
- Pennsylvania State University
- October 27, 2005

## Outline

- Background – UW West-wide hydrologic forecasting system
- Preliminary multi-model ensemble work
- Final Comments

## Background: UW west-wide system

- where did it come from?
- 1997 COE Ohio R. basin/NCEP ->
- -> UW East Coast 2000 (NCEP/ENSO) ->
- -> UW PNW 2001 -> UW west-wide 2003
- what are its objectives?
- evaluate climate forecasts in hydrologic applications
- seasonal:  CPC, climate model, index-based (e.g., SOI, PDO)
- 16-day:  NCEP EMC Global Forecast System (GFS)
- evaluate assimilation strategies
- MODIS snow covered area; AMSR-E SWE
- SNOTEL/ASP SWE
- evaluate basic questions about predictability
- evaluate hydrologic modeling questions
- role of calibration, attribution of errors, multiple-model use
- evaluate downscaling approaches
- what are its components?

## CURRENT WEBSITE

## Surface WaterMonitor

- daily updates
- 1-2 day lag
- soil moisture
- & SWE
- percentiles
- 1⁄2 degree
- resolution
- archive from
- 1915-current
- uses ~2130
- index stns

## Background: UW west-wide system

*** experimental, not yet in real-time product**

## Background: UW west-wide system

***Soil Moisture***
**Initial Condition**

***Snowpack***
**Initial Condition**

## Background: UW west-wide system

- ESP

- ENSO/PDO

- ENSO

- CPC Official Outlooks

- Coupled Forecast System CFS

- CAS

- OCN

- SMLR

- CCA

- CA

- NSIPP/GMAO dynamical model

**VIC Hydrology Model**

**NOAA**

**NASA**

**UW**

- Seasonal Climate Forecast Data Sources

## Background: UW west-wide system

- validation of selected historic streamflow
- simulations

## MAP LINKS TO FLOW FORECASTS

## Background: UW west-wide system

**SWE**

**Soil Moisture**

**Runoff**

**Precip**

**Temp**

- Mar-05
- Apr-05
- May-05

## Background: UW west-wide system

- what drives UW system activities?
- research goals:
- exploration of CPC & NCEP products
- data assimilation of NASA products
- Klamath Basin, Sacramento River (particularly Feather)
- collaborations:
- requests by WA State drought personnel
- Yakima-basin forecasts, Puget Sound
- SW Monitor type hydrologic assessment
- interests of Pagano, Pasteris & Co (NWCC):
- calibrated forecast points in Upper Colorado, upper Missouri R. basin, Snake R. basin
- spatial soil moisture, snow and runoff data
- one-off analyses
- other, e.g., U. AZ project with USBR in lower Colorado basin

## Background: UW west-wide system

- research objectives include:
- climate forecasts
- data assimilation
- hydrologic predictability
- multi-model / calibration questions

## Expansion to multiple-model framework

- ESP

- ENSO/PDO

- ENSO

- CPC Official Outlooks

- Coupled Forecast System CFS

- CAS

- OCN

- SMLR

- CCA

- CA

- NSIPP/GMAO dynamical model

**VIC Hydrology Model**

**NOAA**

**NASA**

**UW**

- Seasonal Climate Forecast Data Sources

**Expansion to multiple-model framework**

## LDAS models

**NOAH**

**MOSAIC**

**SAC**

**VIC**

**Dag Lohmann, HEPEX**

- An LDAS intercomparison conclusion:  Model results, using default parameters, have a wide spread for some states and fluxes. Every model is doing something better than other models in some parts of the country

## Multiple-model Framework

**Multiple-model Framework**

- ESP

- ENSO/PDO

- ENSO

- CPC Official Outlooks

- Coupled Forecast System (CFS)

- CAS

- OCN

- SMLR

- CCA

- CA

- NSIPP-1 dynamical model

**VIC Hydrology Model**

**NOAA**

**NASA**

**UW**

- Multiple Hydrologic Models

**NWS**
**SAC**

**NOAH LSM**

**weightings calibrated via retrospective analysis**

- Schaake Shuffle
- (Clark et al)

- Wood et al., 2002

- NWS: Day et al;
- Twedt et al

- Hamlet et al.,
- Werner et al.

## Multiple-model Framework

- Models:
- VIC - Variable Infiltration Capacity (UW)
- SAC - Sacramento/SNOW17 model (National Weather Service)
- NOAH – NCEP, OSU, Army, and NWS Hydrology Lab
- _Model_		_Energy Balance__	_	_Snow Bands_
- VIC		Yes			Yes
- SAC		No			Yes
- NOAH		Yes			No
- Calibration parameters from NLDAS 1/8 degree grid (Mitchell et al 2004) – no further calibration performed
- Meteorological Inputs: 1/8 degree COOP-based, 1915-2004

## Test Case - Salmon River basin (upstream of Whitebird, ID)- retrospective (deterministic evaluation):  25 year training  20 year validation

## Individual Model Results

## Individual Model Results

**Monthly Avg Flow**

**Monthly RMSE**

## Individual Model Results

- VIC appears to be best “overall”
- Captures base flow, timing of peak flow
- Lowest RMSE except for June
- Magnitude of peak flow a little low
- SAC is second “overall”
- No base flow
- peak flow is early but magnitude is close to observed*
- NOAH is last
- No base flow
- peak flow is 1-2 months early and far too small (high evaporation)

## Combining models to reduce error

- Average the results of multiple models
- Ensemble mean should be more stable than a single model
- Combines the strengths of each model
- Provides estimates of forecast uncertainty

## Computing Model Weights

- Bayesian Model Averaging (BMA) (Raftery et al, 2005)
- Ensemble mean forecast = Σwkfk
- where
- fk = result of kth model
- wk = weight of kth model, related to model’s correlation with observations during training

- Raftery, A.E., F. Balabdaoui, T. Gneiting, and M. Polakowski, 2005.  Using Bayesian Model Averaging to Calibrate Forecast Ensembles.  *Monthly Weather Review*, 133, 1155-1174.

## Computing Model Weights

- We transform flows to Gaussian domain and bias-correct them before computing weights using the BMA software
- Western U.S. – many streams have 3-parameter log-normal (LN-3) distributions for monthly average flow
- Each month, for each model, is given distinct distribution, transformation, bias-correction
- Procedure
- monthly LN-3 transformation
- monthly bias correction based on regression
- BMA process to calculate monthly weights, statistics
- weights used to recombine models
- transform outputs back to flow units

## Multi-model ensemble results

- June

- September

## Multi-model ensemble results

**June Flow, 1975-1995**

**September Flow, 1975-1995**

## Multi-model ensemble results

**June LN-3 & Bias-Corrected Flow, 1975-1995**

**Sept LN-3 & Bias-Corrected Flow, 1975-1995**

## Multi-model ensemble results

## Multi-model ensemble results

## Multi-model ensemble results

## Multi-model ensemble results

## Multi-model ensemble results

- despite large biases, SAC had a stronger interannual correlation with observations than VIC
- post-processing fixes many of the biases
- BMA procedure only really uses the inter-annual signal supplied by the models

## Follow-on questions

- Can we infer anything about physical processes from the ensemble weights?
- How will this work in the ensemble forecast context?
- in gaining forecast accuracy, might we lose the physical advantages of models?
- other ways of applying BMA?  e.g., not monthly timestep; with different bias-correction & transformation

## ongoing work

- RESEARCH -- RESEARCH -- RESEARCH
- assimilation of MODIS & other remote sensing
- climate forecast (CPC outlooks, climate model, index-based)
- downscaling
- shorter term forecasts (GFS-based)
- multiple-model exploration
- further development of SW Monitor
- generally, water / energy balance questions in face of climate change / variability
- HEPEX support

## HEPEX western US/BC testbed

**Test Bed Leaders:**
- Frank Weber (BC Hydro, Burnaby, British Columbia, Canada)
- Andrew Wood (University of Washington, Seattle, USA)
- Tom Pagano (NRCS National Water and Climate Center, Portland, OR)
- Kevin Werner (NWS/WR)
**focus:**
- hydrologic ensemble forecasting challenges that are particular to the orographically complex, snowmelt-driven basins of the Western US and British Columbia...prediction at monthly to seasonal lead times (i.e., 2 weeks t0 12 months).
- 	snow assimilation & model calibration
**basins:**
- Mica (BC), Feather (CA), Klamath (OR/CA), Yakima (WA), Salmon (ID), Gunnison (CO), others?

## END