Investigation of Climate Change Impacts on Water Resources in the California region
D. Cayan1, M. Dettinger2, R. Hanson 2, T. Brown 3, A. Westerling1
1 Scripps Institution of Oceanography
2 US Geological Survey
3 Desert Research Institute

ACPI Progress report  1/19/01
1.  PCM simulations:  extraction and preliminary analyses
      a. Data extracted (monthly and daily average)
          Historical 7 B06.22 (greenhouse CO2+aerosols forcing)  1870-2000
          Climate Change B06.37 (BAU6, future scenario forcing) 2000-2076
          Climate Change B06.40 (BAU6, future sceanrio forcing) 1995-2099
          Climate Change B06.42 (BAU6, future scenario forcing) 1995-2099
      b. Analysis

2.  Effects upon snowmelt-driven watersheds in the Sierra Nevada

      a. statistical downscaling to Sierra watersheds
      b. historical runs, Carson, American, Merced Rivers

3.  Effects upon water resources in California coastal Aquifers

      a. sea level change sensitivity runs

4.  Summer Aridity--Wild Fire impacts

      a. fire danger code
      b. historical wildfire dataset
      c. analysis of variability fire starts vs. climate patterns

Appendix A:  Model Simulation Archive

1. PCM simulations: Data extraction and preliminary analyses
Our efforts towards extracting data from new PCM simulations continues. Currently three new PCM simulations have been completed: B06.40, B06.42 and B06.43. All three of these simulations are Business-As-Usual future scenario forcing simulations. We have extracted the monthly data for B06.40 and B06.42 and are currently extracting the daily average data from B06.40 (Appendix A). We will extract monthly and daily average data from all three simulations. Tables of the variables we are extracting can be found below (Monthly, Daily and 6-Hourly Variable Table in Appendix A).

Our preliminary analyses of the PCM data have focused on the amount of variability and change in the monthly data. We extracted the PCM data along the west coast of the Americas for 20-year periods. Looking at 2m air temperature along the coastal land strip, values continue to warm during the climate change (B06.37) simulation and are generally 1.5 to 2K warmer into the later part of the simulation as compared to the historical (B06.22, years 1870-1969) simulation (Figure 1).

Figure 1:  ONDJFM Land Coastal Strip 2m Air Temperature Anomalies  B06.22 and B06.37

Total winter (ONDJFM) precipitation anomalies are more variable along the coastal strip (Figure 2).

Figure 2:  ONDJFM Land Coastal Strip Total Precipitation Anomalies  B06.22 and B06.37

Some 20-year periods during the climate change simulation appear to be significantly drier than the historical simulation along the US coast which is of concern for our regional investigations. Interestingly, this pattern tends to be symmetrical about the equator, indicating that a global circulation change is involved. The global ONDJFM total precipitation for the period 2059-2075 reveals a split ITCZ with an interesting dipole south of the equator (Figure 3).

Figure 3


2.  Effects upon snowmelt-driven watersheds in the Sierra Nevada

Much of the water supply in California and the western United States is derived from snow melt runoff from mountainous watersheds. To investigate impacts of climate change, we will use the relevant output from ACPI global and regional-downscaled model simulations to drive well-calibrated hydrologic models of selected mountainous watersheds in the Sierra Nevada. These models, which have been run to elucidate variability under present day historical conditions and a range of climate change scenarios, include the Merced River, the North Fork American River, and the Carson River (e.g., Jeton et al., 1996; Dettinger et al., 1998; Wilby and Dettinger, 2000; Miller et al., 1999), and cover a broad range of elevation, exposure to storms, and latitude. Tests to be performed using these models will include:

In order to begin to address these questions and those ennumerated under the other two thrusts (3. and 4. below), we have begun to extract a GCM regional to global model data subset from the PCM historical and climate change simulations archived at the NERSC facility in Berkeley. This set of California-related vaiables is broad enough that it may serve other ACPI application needs as well, and is available upon request.
Parallel Climate Model Historical Simulations of Sierra Nevada Streamflow
Daily precipitation and reference-height temperatures from PCM Historical Simulation #7 (1871 through 1972) have been used as input to precipitation-runoff models of the Merced, Carson, and American Rivers in the Sierra Nevada. These simulations demonstrate the linkages available to use climate-model simulations to project possible hydrologic responses to historical and future climate scenarios.

In order to make the connection between the global-scale climate simulations and the watershed-scale (on order ot 1000 km**2) hydrologic models for this initial demonstration, a simple statistical correction of the grid-scale daily climate series from Historical Run #7 was performed. Because the coupled climate model's historical simulation represents just one realization among the infinite number of possible climate histories in the last century (under historical radiative forcings)--whereas the actual historical climate has represented another, no one-to-one relation can be expected between the simulated and historical precipitation and temperature series over California. Therefore, the simulated climate series were not be expected to directly mimic the weather inputs to the watershed models (which are designed to be driven by time series from local weather stations). Instead, the monthly-mean probability distributions of daily temperatures (maximum and minimum), frequency of wet vs. dry days, and wet-day amounts for the 1951-1972 period from the simulation were mapped onto the observed distributions from the same period. This time period is one in which all three river models had historical observations to allow the proper mappings to be developed.

Figure 4 shows an example of the mapping for one of the weather stations that drives the Carson River model, with black circles corresponding to the observed temperature and precipitation exceedences and the red circles corresponding to the mapped PCM values from a grid cell over Northern California. Notice that the observed and simulated temperatures compare very closely; the mapped, simulated precipitation amounts differ somewhat among the wettest 10 days but otherwise agree very well. The number of wet days in the mapped, simulated series and in the observations are exactly equal. Upon mapping, the lag-one-day correlations of simulated temperatures and precipitation (not shown) are very similar to the observed series over all; this simulated autocorrelation is a direct result of the dynamics in the climate model, as no attempt was made to correct the mappings for antecedent conditions. 

Figure 4

The mappings developed to relate the simulated and observed climate series are then applied--without change--to other parts of the historical simulation and, at least initially, to the subsequent climate-change simulations. One question that arises in this mapping procedure, when applied to COUPLED climate model outputs, is whether the large-scale climate of the model and observations were sufficiently similar during the training period. That is, suppose that the coupled model during the 1950-72 period had been in a different Pacific decadal climate regime than was historically observed. The mappings might then have the effect of making an El Nino-rich model climatology of temperatures and precipitation look like an observed La Nina-rich climatology. Then in other parts of the simulation, when the model became more La Nina-rich, the mappings would possibly overcompensate, making the mapped climatology resemble a super-La Nina decadal period.

As it happened, in the Historical Simulation #7, the 1950-70 period experienced remarkably Pacific decadal climate regimes, at least as measured by the simple index plotted in Figure 5. Consequently, the 1950-70 training period for the Historical Simulation #7 may well be the most appropriate period available.

Figure 5

The daily temperatures and precipitation from the entire Historical Simulation #7, 1871-72, period were mapped to resemble the distributions from the watershed-model input sites using the relations from 1950-72. If during earlier periods, or in later simulations, the character of the daily climate changes, the mappings will ensure that the inputs to the watershed models change accordingly. Upon running the three Sierra Nevada river models with Historical Simulation #7, the resulting streamflow simulations were compared to observed flows (during periods when flow observations were available, and to flows simulated using observed meteorology as inputs.

Figure 6 compares the annual-flood series from observations, simulations with observed meteorology, and simulations with the PCM climate history (#7). The annual-flood series is a series comprising the annual maximum-daily flows at each river. The figure compares exceedence probabilities estimated from the three sources.

Figure 6

The correspondences between observed and simulated flood probabilities are best for the Carson River model. The Merced River model yields relatively similar simulated flood probabilities, but both simulations tend to overestimate the probabilities of the largest floods.Simulated changes in flood frequencies in both the Carson and Merced Rivers, due to greenhouse gases, will probably fall outside the range of differences shown above and thus will be useful. The American River flood probabilities estimated from the PCM history is least like the observed probabilities or the probabilities from simulations with observed meteorology. [The probabilities plotted are based on the entire periods of "record" available in each case; that is, they are based on 100 years of PCM history and anywhere from 12 years (for Carson) to 22 years (for American) to 85 years (for Merced) of observed flows and meteorology.]

Figure 7 compares the observed and simulated monthly flow climatologies of the three rivers. [As before, the full periods of "record" are used in each case.] Comparisons are encouraging, although the Carson simulation with PCM history is generally too wet and the simulated American flows are too early. This tendency may reflect a tendency for wet days to be cooler than dry days overall in the Sierra Nevada, a tendency that has not been explicitly accomodated in the simple weather mappings used here.

Figure 7

These initial simulations encourage us to believe that we will be able to identify and (broadly) quantify the influences of future climate changes simulated by the PCM with the Sierra Nevada river models. The simple "correction" procedure used here may be limiting the results here and certainly may be suspect in the subsequent future-climate investigations. Thus we await eagerly the next-generation downscaled climate scenarios that other parts of ACPI are developing.
It turns out that the period from about 1950 to 1970 (when our copy of the simulated data runs out) the pdo states are in remarkable agreement. This is strictly fortuitous; in the coupled ocean-atmosphere model, there is no particular reason for the actual pdo transitions to line up with the real world, just their amplitudes and periodicities should be similar.


California Applications Program. Web site location:

Dettinger, M.D., Mo, K., Cayan, D.R., and Jeton, A.E., 1999. Global to local scale simulations of streamflow in the Merced, American, and Carson Rivers, Sierra Nevada, California. Preprints, American Meteorological Society's 14th Conference on Hydrology, Dallas, January 1999, 80-82.

Hall, B., T. Brown and J. Roads, 2000. Utilization of Scripps ECPC Forecasts for Regional Monthly Assessments. Proceedings AMS Fireweather Conference. Long Beach, CA.

Jeton, A.E., Dettinger, M.D., and Smith, J.L., 1996. Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada. U.S. Geological Survey Water Resources Investigations Report 95-4260, 44 p.

Knowles, N., 2000. Modeling the Hydroclimatology of the San Francisco Bay-Delta Estuary and Watershed. Ph.D. dissertation, University of California - San Diego, Scripps Institution of Oceanography, 277pp.

Miller, N., Kim, J.W., and Dettinger, M.D., 1999. California streamflow evaluation based on a dynamically downscaled 8-year hindcast  (1988-1995), observations, and physically based hydrologic models. Eos, American Geophysical Union Fall Meeting supplement, v. 80, p. F406.

Wilby, R.L., and Dettinger, M.D., 2000. Streamflow changes in the Sierra Nevada, California, simulated using statistically downscaled general circulation model output. Chapter in "Linking Climate Change to Land Surface Change", S. McLaren and D. Kniveton (eds.), Kluwer Academic Publishers (Netherlands), in press, 20 p.

4.  Effects on summer aridity and fire potential in the California region

Brown, T., 1999. Development of a Southern California Fire Weather Severity Index. Final Report, The Wildfire Hazard Reduction Training and Certification Program, University of California - Berkeley, Forest Products Laboratory, May 1999, 13 pp.

Brown, T.J., and J.L. Betancourt, 2000. Effect of climate variability and forecasting on fuel treatment schedules in the western U.S. Proceedings Joint Fire Science Conference and Workshop, Vol. II, Boise, ID, 15-17 June 1999, University of Idaho and the International Association of Wildland Fire, 167-172.

California Applications Program. Web site location:

Program for Climate, Ecosystem and Fire Applications (CEFA). Web site location:

Westerling, A., 2000. Western United States Fire Climatology. AGU Fall Meeting, December 15-19, San Francisco.

Appendix A:  Model Simulation Archive
Data Time Step
Period Available
Period Retrieved
Historical GS Forcing 7 (B06.22, B06.30) Daily 1870-1999 1870-1972
Historical GS Forcing 7 (B06.30) 6-hourly 1974-1996 not yet
Historical GS Forcing 7 (B06.22) Monthly 1870 - 1999 1870-1972
Business-As-Usual 6 (B06.31, B06.32, B06.37) Daily 2019-2095 2019-2075
Business-As-Usual 6 (B06.31, B06,32) 6-hourly 2019-2051; 2075-2095 2048-2051
Business-As-Usual 6 (B06.37) Monthly 2019 - 2095 2019-2075
Business-As-Usual 6 NEW 
Monthly; Daily 1995-2099 1995-2099;1995-2050
Business-As-Usual 6 NEW 
Monthly; Daily 1995-2099 1995-2076; NA
Business-As-Usual 6 NEW 
Monthly; Daily 1995-2099 NA; NA
Note that even though the 6-hourly and daily data were saved under different simulation names, the simulations are identical bit-for-bit.

We have also archived data from run B05.03 (Historical 1 simulation; PCM1.1 Historical GHG + SO4 Scenario).

Daily Variables
Net Longwave Radiation Flux at the Surface flns W/m**2
Downward Shortwave Radiation Flux at the Surface fsds W/m**2
Net Shortwave Radiation Flux at the Surface fsns W/m**2
Latent Heat Flux at the Surface lhfl W/m**2
Mean Sea Level Pressure mslp Pa
Convective Precipitation prcc m/s
Large-scale Precipitation prcl m/s
Sensible Heat Flux at the Surface shfl W/m**2
Maximum Reference Height Temperature tmax K
Minimum Reference Height Temperature tmin K
500mb Geopotential Height z500 m
700mb Geopotential Height z700 m
Note all data are in global T42 arrays. T42 global resolution is 128 longitudes by 64 latitudes.
6-Hourly Variables
Specfic Humidity (19 levels) qall kg/kg
Temperature (19 levels) tall K
Zonal Wind (19 levels) uall m/s
Meridional Wind (19 levels) vall m/s
Surface Pressure psfc Pa
Radiative Flux absorbed at the Surface srad W/m**2
Note all data are in T42 arrays over the region 54N to 10N and 160W to 90W.
Monthly Variables
CO2 Volume Mixing Ratio co2v m**3/m**3
Net Longwave Radiation Flux at the Surface flns W/m**2
Downward Shortwave Radiation Flux at the Surface fsds W/m**2
Net Shortwave Radiation Flux at the Surface fsns W/m**2
Convective Precipitation prcc m/s
Large-scale Precipitation prcl m/s
850mb Specific Humidity q850 kg/kg
Surface Specific Humidity qbot kg/kg
Surface Runoff rosf mm/s
Sub-surface Runoff ross mm/s
Root-zone Volumetric Soil Water sowa fraction
Reference Height Temperature ta2m K
East-West Surface Stress taux N/m**2
North-South Surface Stress tauy N/m**2
Surface Zonal Wind Component ubot m/s
Surface Meridional Wind Component vbot m/s
500mb Geopotential Height z500 m
700mb Geopotential Height z700 m
Note all data are in global T42 arrays. T42 global resolution is 128 longitudes by 64 latitudes.