1. Seasonal outlooks for hydrology and water resources: streamflow forecasts for the Columbia River basin
Andrew Wood
Alan Hamlet
Marketa McGuire
Dennis Lettenmaier
University of Washington
The Climate Impacts Group Annual Fall Forecast Meeting
Kelso, WA October 14, 2003
important points:
Arun Kumar works for the NCEP Environmental Modeling Center, Climate Modeling Branch and runs the global spectral model to produce forecasts.
this study period and region are important because there is an evolving drought that we would like to use as a test situation for the method’s skill.
this approach was previously applied to the East Coast during Summer 2000, when there was an evolving drought in that region – a paper evaluating the project is currently submitted to JGR-Atmospheres.

2. S/I Hydrologic Forecasting Project

3. Goals of UW Forecasting Project
Produce real-time ensemble forecasts:
based on experimental climate model forecast products
based on established methods (such as ESP)
of streamflow, for selected large river basins (primarily in the West)
of snowpack / soil moisture anomalies
Assess experimental product skill relative to established forecast products
Evaluate relative hydrologic prediction skill due to ICs - initial land surface conditions (soil moisture, snow) and due to climate forecast skill.

4. Outline Project Overview hydrologic model-based approach
spin-up: initial condition estimate
suite of climate forecasts
Last year’s forecast results (brief review)
Current Columbia River basin forecasts
initial conditions
hydrologic forecasts
reservoir forecasts
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

5. Overview: VIC Hydrologic Model
important point(s):
VIC is a water & energy balance with some subgrid scale approximations for vegetation, elevation and soil dynamics, and has a crude routing that works as a post processor.
VIC has been applied to a number of continental scale river basins around the world and is well documented in the literature.

6. Overview: Hydrologic Modeling
Simulations for 1950-current climatology, presently extending back to 1915-current
Five major basins
~100 streamflow locations, currently

7. Model-based Forecasting Approach
General
streamflow,
soil moisture,
snowpack,
runoff
local scale weather inputs
forecast ensemble
meteorological sequences
downscaling process *
hydrologic simulation
* for climate model
forecasts
VIC Hydrology Model
1/8 degree resolution
daily P, Tmin, Tmax
NASA NSIPP-I Forecasts
2-2.5 degree resolution
monthly total P, avg T
NCEP GSM Forecasts
1.9 degree resolution
Experimental forecast applications
important point(s):
the overall forecasting approach involves using forecast model (the global spectral model) T & P output at a coarse timestep & scale as hydrologic model input at a finer timestep and scale.
to make a hydrologic forecast, you need a transformation of the forecasts that first overcomes climate model bias and the scale differences, then simulates the water balance.
also, GSM is really run at very fine timestep (~5-15 minutes) but only the monthly anomalies are archived for our use. most of the signal is at the monthly scale, however, so this is acceptable.

8. Overview: VIC Simulations
Forecast Products
streamflow
soil moisture
runoff
snowpack
derived products
VIC model spin-up
forecast ensemble(s)
climate forecast information
climatology ensemble
1-2 years back
start of month 0
end of mon 6-12
NCDC met. station obs. up to 2-4 months from current
LDAS/other real-time met. forcings for remaining spin-up
data sources
snow state information
important point(s):
after bias correcting and downscaling the climate model forecasts, the procedure for producing hydrologic forecasts is as follows:
we spin up the hydrologic model to the start of the forecast using observed met. data (from 2 sources: NCDC cooperator stations through 3-4 months before the start of the forecasts, then LDAS 1/8 degree gridded forcings thereafter).
The GSM forecasts comprise 2 sets of ensembles, one for climatology and one for the forecast. The climatology ensemble yields a distribution of the conditions we’ve seen over the period , while the forecast ensemble yields the distribution of the conditions we might see for the next 6 months. Although the climatology ensemble is nominally unbiased against a simulated climatology based on observed met. data (rather than bias-corrected, downscaled GSM met. forcings), we compare the forecast and GSM climatology so that any unforeseen biases (resulting, perhaps, from the downscaling method) occur in both climatology and forecast. Eventually this cautionary step may be eliminated, and we’ll compare directly to the simulated observed climatology.
at the end of the spin-up period and one month before month 1 (out of 6) of the forecasts, we save the hydrologic model state. The state is then used for initializing the forecast runs. Through the first month, the model runs on observed data to the last date possible, then switches to the forecast data. Usually, we process the observed forcings up through the 15th to 25th of this initialization month, then the forecast forcing data carries the run forward for the remaining days in the month, and throughout the following 6 month forecast period. Note, the state files used for the climatology runs correspond to the spin-up associated with the particular year (out of ) from which the climatology ensemble member is drawn.
the spin-up period captures the antecedent land surface hydrologic conditions for the forecast period: in the Columbia basin, the primary field of interest is snow water equivalent.
forecast products are spatial (distributed soil moisture, runoff, snowpack (swe), etc.), and spatial runoff + baseflow is routed to produce streamflow at specific points, the inflow nodes for a management model, perhaps.

9. Overview: Spin-up approach
Problem: For most recent months, meteorological data availability is poor
1-2 years before start date: dense station network (~1000), forcings
consistent with those used in model
calibration, etc. (mostly COOP stations)
2-2.5 months prior to start: coarse reporting network (~150 stns, some COOP)
density lower in Canada.
Solutions:
> LDAS 1/8 degree real-time forcings from NOAA/NASA
> Index station method: combine coarse network signals with dense station
climatology
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

10. Overview: Spin-up approach, Index Stn Method
1. interpolate monthly percentiles from sparse index stations to 1/8 degree grid
2. find percentiles’ matching amounts in the dense station-derived climatology
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

11. Overview: Spin-up approach, Index Stn Method
Example for monthly precipitation
percentiles interpolated to 1/8 degree grid
pcp percentile
matching 1/8 degree pcp amts
Index stn pcp
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.
lastly, daily seqences from stations applied to monthly grid cell totals, and rescaled to produce estimated monthly amounts.

12. Overview: Initial snow state assimilation
Problem:
index station method incurs some bias, but snow/SM state estimation is critical
Solution:
use SWE observations (from the 600+ station USDA/NRCS SNOTEL network and several ASP stations in BC, Canada, run by Environment Canada) to adjust snow state at the forecast start date
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

13. Overview: Suite of Forecasts
Ensemble Streamflow Prediction (ESP)
ESP method with ENSO and ENSO/PDO compositing
Climate model-based forecasts
CPC official forecasts (still in development)
important point(s):
GSM forecasts take the form of monthly ensembles of length 6 months
we get them early in each month for a start date of the following month.
the climatology ensemble enables us to define the climate model bias and correct it
climatology ensembles run out 6 months just like the forecasts, but use observed rather than predicted tropical Pacific SSTs
also:
210 ensembles for GSM climatology are derived from observed SSTs in each year of the 21 year climatology period ( ) combined with 10 initial atmospheric conditions for each year
GSM is at T42 spatial resolution, but moving to T62 soon (resolution improvement of about 1/3)

14. Overview: 1. ESP method NWS River Forecast Center (RFC)
approach: rainfall-runoff modeling
(i.e., NWS River Forecast System,
Anderson, 1973
offspring of Stanford Watershed Model, Crawford & Linsley, 1966)
Ensemble Streamflow Prediction (ESP)
used for shorter lead predictions;
a variation is used for longer lead predictions
The RFC final seasonal
forecasts also incorporate
NRCS results.
ICs
Spin-up
Forecast
obs
RMSE
recently observed
meteorological data
ensemble of met. data
to generate forecast
ESP forecast
hydrologic
state

15. Overview: Hydrologic prediction, an aside
active
Snow water content on April 1
should add my personal pics of -
snow sampling
snotel sites
(and scan in curve method figure)
SNOTEL network
NRCS SNOTEL Network
McLean, D.A., 1948 Western Snow Conf.
April to August runoff

16. Overview: 2. ESP-based composites
Columbia River at The Dalles, OR
Blue = all years
Green = all enso neutral (33)
Red = enso neutral (12)

17. Overview: 3. Climate model-based forecasts
Seattle

18. Overview: Climate model-based forecasts
Previously, demonstrated our approach for combining seasonal climate model forecasts with hydrologic simulation to create hydrologic forecasts
Climate Model: NCEP Global Spectral Model (GSM)
Hydrology Model: VIC (at 1/8 or 1/4 degree resolution)
Real-time experimental applications:
East Coast (Spring-Summer 2000, November 1997)
(paper: Wood et al. (2001), JGR)
Columbia R. basin (Spring-Summer 2001)
Columbia R. basin (Winter-Spring 2003)
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

19. Overview: 3. Climate model-based forecasts
bias-correcting…
then downscaling…
CRB domain, June precip

20. Overview: 3. Climate model-based forecasts
…and temporal disaggregation
VIC-scale monthly
Tavg forecast

21. Overview: 3. Climate model-based forecasts

22. Overview: 4. CPC Official Forecasts (seasonal)
Note: Consensus forecasts based on a number of methods
CANONICAL CORRELATION ANALYSIS
COMPOSITE ANALYSIS
OPTIMAL CLIMATE NORMALS METHOD
CONSTRUCTED ANALOG ON SOIL MOISTURE
SCREENING MULTIPLE LINEAR REGRESSION
CLIMATE MODEL

23. Overview: CPC Official Forecasts (seasonal)

24. Forecast Results: A quick look at last year
Updates
Dec 28, 2002
Jan 15, 2003
Feb 1
Feb 15
Mar 1
Mar 16
Apr 1
ESP
ESP, GSM, NSIPP
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

25. Last year: Initial Conditions
Dec 28, 2002
Jan 15, 2003
This past winter, we had
alarmingly low PNW December snowpacks
Many areas recovered by April, but not the Cascades
Feb 1, 2003
Mar 1, 2003
Apr 1, 2003
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

26. Last year: streamflow (ESP/NSIPP/GSM)
Dec 1
ESP and climate model forecasts were fairly similar, all reflecting the low moisture initial conditions
Apr 1

27. Last year: UW/NRCS comparison
UW pilot results were comparable to the official streamflow forecasts of the National Resources Conservation Service (NRCS) streamflow forecast group.
Note: estimate given by Jun 1 NRCS forecast
UW pilot forecasts halted

28. Last year: UW/NRCS comparison
ensemble median flow
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

29. Current Columbia River basin forecasts
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

30. Current Forecasts: Initial Conditions
CPC Percent of Normal Precip
September 25, 2003
Jun-Jul-Aug %
Sep
important point(s):
the approach attempts to make use of forecast skill from 2 sources:
better understanding of synoptic scale teleconnections and the effects of persistence in SSTs on regional climate, as reproduced in coupled ocean-atmosphere models;
the macroscale hydrologic model yields an improved ability to model the persistence in hydrologic states at the regional scale (more compatible with climate model scales than prior hydrologic modeling).
Climate forecasts with monthly and seasonal horizons are now operationally available, and if they can be translated to streamflow, then they may be useful for water management.

31. Current forecasts: streamflow (ESP-based)

32. Current forecasts: streamflow (ESP-based)

33. Current forecasts: streamflow (ESP-based)

34. Current forecasts: streamflow (ESP-based)

35. Current forecasts: streamflow (ESP-based)

36. Current forecasts: Reservoir system storage
Simulated streamflows
Reservoir model inputs
Unconditional ESP
ENSO-neutral forecast
Full Pool
ensemble mean

37. Current forecasts: Snake River locations
Upper Snake Storage Forecast

38. Current forecasts: Reservoir system storage
Unconditional ESP
System Storage Forecast from SnakeSim includes:
Jackson Lake
Palisades
Island Park
Ririe
American Falls
Lake Walcott
Full Pool
ensemble mean

39. Current forecasts: Still to come
Products in development:
spatial forecasts of
SWE, Runoff and SM, e.g.
expanding to
rest of the West
improved spin-up procedure
retrospective forecast
verification

40. Conclusions
Currently normal to slightly low soil moisture conditions in the runoff producing areas east of Cascades; very low west of Cascades
Streamflow forecasts for summer 2004 appear close to normal in most locations
Subsequent forecasts are worth waiting for:
improved initial condition estimation as snow, SM rebuild
methodological improvements