1. POTENTIAL IMPACTS OF CLIMATE CHANGE ON WATER RESOURCES: Accelerated Climate Prediction Initiative (ACPI) Results for the Columbia River Basin
Dennis P. Lettenmaier
Department of Civil and Environmental Engineering
University of Washington
Presentation to
Northwest Power Planning Council
December 12, 2002

2. Outline of this talk Climate variability and change context
Prediction and assessment approach
Accelerated Climate Prediction Initiative (ACPI)
Hydrology and water management implications for Columbia River Basin
Conclusions and comparative analysis

3. 1) Climate variability and change context

4. Humans are altering atmospheric composition
Methane has increased 151%, nitrous oxide 17%, also greenhouse gases

5. The earth is warming -- abruptly
What it is: Average surface temperature year by year
3 main features:
warming to 1940
cooling
warming since 1970
causes of these are different
were generally warmer than the top dots shown (continuing warming trend)

6. Natural Climate Influence Human Climate Influence
Red: observations of global average temperature
Grey: simulations with a climate model (huge computer program, like weather prediction model only run for hundreds of years)
Natural influence: volcanoes, solar variations – guesses before ~1970, better since then
Human influence: greenhouse gases, sulfate aerosols
it is possible to simulate the climate of the last 100 years, and the conclusion is that humans didn’t matter much before 1960 – the early warming and the cooling were largely natural, and the late-century warming was largely human-caused
All Climate Influences

7. The IPCC used a wide range of assumptions about future economic development, from rapid global economic growth relying mostly on fossil fuels to slow growth in which the developed world goes heavily toward a service economy and the developing world is left behind. For this wide range, CO2 doubles between 2050 and Best guess: 1C by mid-century, 3C by 2100.
Note that constant global temperature is not among the projections

8. Temperature trends in the PNW over the instrumental record
Almost every station shows warming (filled circles)
Urbanization not a major source of warming
BC: 0.5C (0.9F) in coastal region and 1.1C (2F) in CRB

9. Trends in timing of spring snowmelt (1948-2000)
+20d later
–20d earlier
Courtesy of Mike Dettinger, Iris Stewart, Dan Cayan

10. Trends in snowpack

11. This shows 10-year averages of temperature for the whole PNW; 1990’s were the warmest decade of the 20th century in the Northwest (as well as globally), by almost 1 degree. The rate of warming from 1970 to 2000 has been roughly what the CGCM1 simulates.
We looked at 8 scenarios produced by several different general circulation models from climate modeling centers around the world. All used the same simple scenario for CO2: 1%/year. The spread here does not include the spread from other greenhouse gas scenarios.
Looking ahead to the 2020s and 2040s, the warmest, average, and coolest of these 8 models are shown as red, yellow, and green. The average rate of warming is a bit less than 1 degree per decade. Even the coolest scenario still shows about 2F more warming by the 2040s.

12. 2) Prediction and assessment approach

13. Global climate simulations, next ~100 yrs
Scenarios
Performance
Measures
Downscaling
Global climate simulations, next ~100 yrs
Delta
Precip,
Temp
Reliability
of System
Objectives
Reservoir
Model
Hydrologic
Model (VIC)
DamReleases,
Regulated
Streamflow
Natural
Streamflow

14. Coupled Land-Atmosphere-Ocean General Circulation Model
Reservoir
Model
Hydrology Model

15. Bias Correction and Downscaling Approach
climate model scenario
meteorological outputs
 hydrologic model inputs
snowpack
runoff
streamflow
2.8 (T42)/0.5 degree resolution
monthly total P, avg. T
1/8-1/4 degree resolution
daily P, Tmin, Tmax
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.

16. Bias Correction
from NCDC observations
from PCM historical run
raw climate scenario
bias-corrected climate scenario
month m
Note: future scenario temperature trend (relative to control run) removed before, and replaced after, bias-correction step.

17. interpolated to VIC scale
Downscaling
observed
mean fields
(1/8-1/4 degree)
monthly PCM
anomaly (T42)
VIC-scale
monthly simulation
interpolated to VIC scale

19. Overview of ColSim Reservoir Model
Reservoir Operating Policies
Reservoir Storage
Regulated Streamflow
Flood Control
Energy Production
Irrigation Consumption
Streamflow Augmentation
Physical System
of Dams
and Reservoirs
Streamflow Time Series

20. Dam Operations in ColSim
Storage Dams
Virgin
Regulated
Run-of-River Dams
Flow In=Flow out + Energy H

21. ColSim Storage Reservoirs + Run of River Reservoirs
Releases Depend on:
Storage and Inflow
Rule Curves (streamflow forecasts)
Flood Control Requirements
Energy Requirements
Minimum Flow Requirements
System Flow Requirements
Inflow
ColSim
Consumptive use
Inflow
Inflow
Consumptive use
Inflow
Inflow
Inflow +
Inflow
Run of River Reservoirs
(inflow=outflow + energy)
System Checkpoint

22. 3) Accelerated Climate Prediction Initiative (ACPI)

23. Accelerated Climate Prediction Initiative (ACPI) – NCAR/DOE Parallel Climate Model (PCM) grid over western U.S.

24. Climate Change Scenarios
PCM Simulations (~ 3 degrees lat-long)
Historical B06.22 (greenhouse CO2+aerosols forcing)
Climate Control B06.45 (CO2+aerosols at 1995 levels)
Climate Change B06.44 (BAU6, future scenario forcing)
Climate Change B06.46 (BAU6, future scenario forcing)
Climate Change B06.47 (BAU6, future scenario forcing)
PNNL Regional Climate Model (RCM) Simulations (~ ¾ degree lat-long)
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)
Climate Control B06.45 derived-subset
Climate Change B06.44 derived-subset

25. Future streamflows 3 ensembles averaged summarized into 3 periods;

26. Regional Climate Model (RCM) grid and hydrologic model domains
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.

27. ACPI: PCM-climate change scenarios, historic simulation v air temperature observations

28. ACPI: PCM-climate change scenarios, historic simulation v precipitation observations

29. 4) Hydrology and water management implications: Columbia River Basin

30. PCM Business-as-Usual scenarios Columbia River Basin (Basin Averages)
BAU 3-run average
historical ( )
control ( )
PCM
Business-as-Usual
scenarios
Columbia River Basin
(Basin Averages)
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

31. RCM Business-as-Usual scenarios Columbia River Basin (Basin Averages)
PCM BAU B06.44
RCM BAU B06.44
control ( )
historical ( )
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.

33. PCM Business-As-Usual Mean Monthly Hydrographs Columbia River Basin
@ The Dalles, OR
important point(s):
we’re modeling most of the US at 1/8 degree now with the VIC model, but we are performing this forecasting exercise in the Columbia River basin. The plusses show the grid of the numerical weather prediction (forecasting) model that we used (GSM), and the ¼ degree hydrology model resolution can just be discerned in the figure. 24 climate model grid points were used, and 1,668 VIC model cells. We’ve aggregate the VIC model to ¼ degree from 1/8 degree in the Columbia River basin to speed the forecast runs.
month
month

34. CRB Operation Alternative 1 (early refill)

35. CRB Operation Alternative 2 (reduce flood storage by 20%)
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
45,000,000
50,000,000
55,000,000 O N D J F M A S
End of Month Total System Storage (acre-feet)
Max Storage
Control
Base Climate Change
Change (Alt. 2)
Dead Pool

36. CRB Operation Alternative 3 (allocate more storage for fish)
All US + Canadian
Current Operations

38. McNary Flow Deficit
McNary Flow Reliability

39. McNary Flow Deficit
McNary Flow Reliability

42. Trade-Offs Early Refill

43. Trade-Offs for Storage Allocation

44. Trade-Off Curves for Alternative 3
Period 1

45. Trade-Off Curves for Alternative 3
Period 2

46. Trade-Off Curves for Alternative 3
Period 3

47. 5) Summary evaluation and conclusions
Period 1
Firm power is reduced by the system’s inability to meet current hydropower demands without compromising other operating goals (especially instream flows).
Total hydropower production and revenue is relatively unaffected (occasionally increasing) under the projected climate changes.
However, fish flow targets would be difficult to meet under altered climate, and mitigation by altered operation is essentially impossible in late summer.
Although the monthly time step used in this study complicates evaluation of changes in flood risk, the current flood rules appear to be overly conservative, and flood control begins to compete with other water management considerations as hydrographs shift from spring towards winter.