A projection of the cold season hydroclimate in California in mid-21st
century under the SRES-A1B emission scenario

J. Kim^1^, D. Waliser^2^, R. Fovell^1^, A. Hall^1^, K. Liou^1^, Y.
Xue^1^, J. McWilliams^1^, Y. Chao^2^, A. Eldering^2^, Q. Li^1^ and S.
Kapnick^1^

^1^University of California Los Angeles, Los Angeles, CA

^2^Jet Propulsion Laboratory/California Institute of Technology,
Pasadena, CA

Abstract

A projection of the cold season regional climate change signals in the
surface hydroclimate fields corresponding to the mid-21st century in
California has been performed using the dynamical downscaling method in
which a global climate scenario generated by the National Center for
Atmospheric Research (NCAR) Community Climate System Model-3 (CCSM-3) is
downscaled using a regional climate model (RCM) on the basis of the
Weather Research and Forecast (WRF) model. The global climate scenario
is based on the Intergovernmental Panel for Climate Change (IPCC)
Special Report on Emission Scenarios (SRES) A1B emission profile. The
cold season covers a 6-month period that includes fall
(October-December: OND) and winter (January-March: JFM). Regional
climate change signals are calculated as differences between the RCM
climatology for two 20-year periods comprising of the late 20th century
(1961-1980) and the mid-21st century (2035-2054). The results show that
the low-level temperature in California is anticipated to increase by
1-2.5K with larger increases in high elevation regions and in winter.
Noticeable decreases in snowfall, snow-water equivalent (SWE), and
surface albedo in high elevation regions in the projected mid-21st
century climate suggest that temperature increases in high elevation
regions are partially amplified by local feedback through snow and
surface albedo. Precipitation decreases over the entire cold season. The
precipitation change signals show well defined interseasonal variations;
a pattern of positive (negative) signals in the northern (southern)
California region during fall is reversed in winter. The seasonal
variations in the precipitation change pattern are primarily associated
with climate change signals in rainfall. Snowfall decreases in the
warmer climate, most noticeably in winter. The statistical significance
of the projected changes in the low-level temperature and the seasonal
snowfall exceeds the 90% level, with the largest values in high
elevation regions. The statistical significance of the precipitation and
rainfall change signals are lower than the temperature and snowfall
change signals. Changes in seasonal precipitation result in reduction in
snowmelt, seasonal-mean SWE, and runoff during the cold season,
especially in high elevation regions. Decrease in the high elevation
snowpack is of a special concern as it is among the main sources of warm
season water supply in California.

1\. Introduction

The impact of the global climate change induced by the increase in
atmospheric greenhouse gases (GHGs) on the cold season hydroclimate is
an important concern for California. Studies on recent climate
variability (IPCC 1995, 2007) found that the increase in GHG has already
begun altering global and regional climates. The climate of the
California region is characterized by extreme contrasts in precipitation
with wet cold seasons and dry warm seasons. Moreover, California relies
heavily on cold season precipitation for the water supply in the dry
warm seasons. Previous studies (e.g., Dettinger and Cayan 1995; Stewart
et al. 2005) revealed that global climate change appears to be affecting
the snowpack and snowmelt-driven runoff in California\'s mountainous
region. The water supply in California has been marginal for supporting
its large population and industries, especially agriculture. Thus,
reliable assessments of the impact of the climate change on the future
water resources in the region has been an important concern to the water
managers in California (Anderson et al. 2008).

Existing climate change studies strongly suggests that the water
resources in California may be adversely affected by the global climate
change induced by the increase in GHGs (Leung and Ghan 1999; Kim 2001,
2004; Kim et al. 2002; Cayan et al. 2008). Details of the regional-scale
climate change signals, however, vary among the projections according to
emission scenarios, GCMs and RCMs. All projections based on either
statistical or dynamical downscaling of various GCM scenarios agree that
the increase in the low-level air temperatures and earlier melting of
the Sierra Nevada snowpack will occur under higher GHG concentration.
There, however, exist significant differences in precipitation. For
example, the climate change study of Leung and Ghan (1999) which is
based on the dynamical downscaling of an NCAR Community Climate Model
(CCM3) global climate scenario using the MM5 model projected decreases
in winter precipitation in California under the warmer climate
condition. On the contrary, the climate change study by Kim et al.
(2002) which is based on the dynamical downscaling of the Hadley Centre
Climate Model (HadCM2) data using the Mesoscale Atmospheric Simulation
(MAS) model projected increases (decreases) in winter precipitation in
northern (southern) California. The differences between these two
studies are consistent with the differences in the projected
precipitation changes between the two GCMs, at least qualitatively. In
fact, regional precipitation changes are among the most uncertain
results in the existing global climate change studies (IPCC 2007). The
large uncertainties in the projected climate change signals cause
difficulties in developing a plan to adapt to and mitigate the impacts
of climate change. Despite large uncertainties in the GCM projections,
only a limited number of regional climate change studies have been
performed for the California region.

Obtaining climate projection data suitable for assessing the impact of
climate change on water resources in California has been difficult.
Typical resolutions of GCMs that are used to simulate future climate are
of on the order of 100km. With such a horizontal resolution, GCM
simulations cannot account for the effects of regional orography that
plays a crucial role in shaping the climate in California (Kim 2001;
Kyriakidis et al. 2001; Kim and Lee 2003). Thus, downscaling of
GCM-generated climate data to a spatial resolution suitable for
regional-scale features is an essential step in the assessment of the
impact of climate change (Giorgi et al. 1994; Kim et al. 2001; Cayan et
al. 2007). Spatial downscaling of GCM data employs either statistical
(e.g., Wood et al. 2002, 2004) or dynamical (e.g., Giorgi et al. 1994;
Leung and Ghan 1999; Kim et al. 2002) methods. Both methods have their
own advantages and drawbacks. For example, statistical downscaling which
has been widely used in surface hydrological applications (e.g.,
Gershunov and Cayan 2003; Wood et al. 2002) is relatively inexpensive in
terms of computational resources to perform but the physical and
dynamical consistencies among the downscaled variables are not
guaranteed. Moreover, in climate change projections, validity of the
method relies on an assumption that the relationships between the
predictors and the predictands derived in the present climate are valid
in future climate. Compared to statistical downscaling method, dynamical
downscaling using a regional climate model (RCM) is computationally much
more expensive, but can preserve the physical and dynamical
consistencies among the downscaled variables. In addition, simulation
skill varies significantly among RCMs, often resulting in large
differences between the downscaled variables based on different RCMs
(Duffy et al. 2006). Despite its current shortcomings, rapid progress in
model formulations and faster computers makes dynamical downscaling an
important tool for generating future climate data for regional impact
assessment efforts.

This study investigates the impact of the climate change associated with
increased greenhouse gases on the surface hydroclimate in California by
dynamically downscaling a global climate scenario generated by the NCAR
CCSM3 on the basis the IPCC SRES-A1B emission profile. Details on the
experiment are presented in Section 2. Sections 3-6 present the climate
change signals in the key surface hydroclimate during the cold season.
Summary and conclusions are presented in Section 7.

2\. Experiment

The dynamical downscaling was performed using the Weather Research and
Forecast (WRF) model, version 2.2.1 (Skamarock et al. 2005). The model
solves a non-hydrostatic momentum equation in conjunction with
thermodynamic energy equation. Numerically, the model features multiple
options for the advection scheme and the parameterized atmospheric
physical processes. In conjunction with one-way and/or interactive self
nesting capability, this allows us to apply the model to simulate
atmospheric circulation of a wide range of spatial scales. More details
of the WRF model can be found in the web site http://wrf-model.org. The
physics options selected in this experiment includes the NOAH
land-surface scheme (Chang et al. 1999), the simplified Arakawa Schubert
(SAS) convection scheme (Hong and Pan 1998), the RRTM longwave radiation
scheme Mlawer et al. 1997), Dudhia (1989) shortwave radiation, and the
WSM 3-class with simple ice cloud microphysics scheme. For more details
on the physics options, readers are referred to the web site
http://wrf-model.org.

![](media/image1.png){width="2.7in" height="3.3in"}

Figure 1. The model terrain (m) of the 36km resolution western US domain
(outer box). The inner box represents the area where the climate signals
obtained this study are presented. The 5 California sub-regions are
marked by colored rectangles.

The model domain covers the western United States at a 36km horizontal
resolution (Fig. 1), and has 28 atmospheric and 4 soil layers in the
vertical. Also shown in Fig. 1 are the 5 sub-regions selected according
to precipitation characteristics (Table 1). Among these sub-regions, the
three regions, SH, NS, and SS feeds most of major reservoirs that
supplies water in California.

Table 1. Precipitation characteristics in the 5 California sub-regions
in Fig. 1.

  ------------------------- ------------------- ------------ ---------------
  Region                    Elevation Range     Rainfall     Snowfall

  Northern Coastal Range    0-1500m             Heavy        Light
  (NC)                                                       

  Southern Coastal Range    0-1000m             Heavy        Insignificant
  (SC)                                                       

  Mt. Shasta (SH)           500-1500m           Heavy        Heavy

  Northern Sierra Nevada    500-2000m           Heavy        Heavy
  (NS)                                                       

  Southern Sierra Nevada    500-3000m           Heavy        Heavy
  (SS)                                                       
  ------------------------- ------------------- ------------ ---------------

The regional climate simulations were driven by the global climate data
generated by the NCAR CCSM3 according to the SRES-A1B emission scenario
(Nakicenovic et al. 2000). The emission scenario assumes balanced energy
generation between fossil and non-fossil fuel; the resulting CO~2~
emissions located near the averages of all SRES emission scenarios. The
climatology for the late 20th century and mid-21st century periods is
calculated from the 20 cold season (October-March) regional simulations
for 1961-1980 and 2035-2054, respectively. The CO~2~ concentrations in
the WRF simulations were fixed at 330ppmv and 430ppmv during the
present-day and mid-21st century periods, respectively. A schematic
illustration of the data flow is presented in Figure 2. Individual runs
were initialized at 00UTC October 1 of the corresponding years using the
CCSM-3 output data. All simulations continued for the remaining 6 month
period without re-initialization by updating the large-scale forcing
along the lateral boundaries at 3-hour intervals.

![](media/image2.png){width="3.85in" height="2.002083333333333in"}

Figure 2. The information flow in the experiment

In the following, the impact of increased greenhouse gases on the key
surface hydroclimate fields in the California region is presented in
terms of the climate change signals. The climate change signal in a
variable is defined as the difference in the 20-year climatology of the
variable between the mid-21st century and the late 20th century periods.
The hydroclimate fields examined in this study include the near-surface
air temperature, precipitation and its partitioning between rainfall and
snowfall, runoff, snowmelt, and the high elevation snowpack. These
variables play crucial roles in shaping water resources, hydropower
generation, and ecosystem in the region stability.

3\. The changes in the low-level air temperature

Increases in the low-level air temperatures by 1.0-2.5K in California
(Figure 3a) are projected for the entire cold season (October-March).
The warming signals are largest in the high elevation regions in the
Sierra Nevada and are smallest in the coastal regions and in the Central
Valley. The projected warming signals are similar to the results in
previous studies for the region on the basis of various global and
regional climate models (Giorgi et al. 1994; Kim et al. 2002; Leung et
al. 2004; Duffy et al. 2006) in their spatial pattern and the magnitude.
The strong gradient in the warming signal between the coastal and
mountain/inland regions results chiefly from two factors; the prevailing
westerly winds advecting the mean ocean-land gradient during the cold
season and the reduction in surface albedo associated with smaller snow
cover in the high elevation regions in the warmer climate (Kim et al.
2002). The statistical significance of the projected temperature signals
exceeds 90% except in the Central Valley region.

![](media/image3.png){width="5.1in" height="2.542361111111111in"}

Figure 3. The low-level temperature change signals in the California
region over; (a) the entire cold season (October-March), (b) fall
(October-December: OND) and (c) winter (January-March: JFM).

The projected low-level temperature changes show noticeable differences
between the early (fall: OND) and the late (winter: JFM) cold season
(Fig. 3b,c). The projected temperature changes in the California region
are as large as 2K for fall with larger increases in the southeastern
California (Fig. 3b). Much larger temperature increases, 1.5-3K, are
projected for winter with the largest values occurring over the Sierra
Nevada and the southeastern part of the state (Fig. 3c). The differences
in the surface albedo between the mid-21st century and the late 20th
century runs (Fig. 4) reveal significant reduction in the surface albedo
over high elevation regions including the Sierra Nevada and the Mt.
Shasta regions, especially in the later half of the cold season (JFM).
The projected climate change signals in the low-level temperature and
surface albedo shows that the link between the low-level temperature
changes and the changes in surface albedo appears to be especially
strong in high elevation regions.

![](media/image4.png){width="5.1in" height="2.55in"}

Figure 4. The percent changes in surface albedo for (a) entire cold
season (October-March), (b) fall (OND) and (c) winter (JFM).

The mean temperature changes over the 5 sub-regions in California (Table
2) show that the projected warming signal is larger in winter than in
fall. The locations of the 5 sub-regions are shown in Fig. 1. The
largest warming signals occur in the Mt. Shasta, the northern Sierra
Nevada, and the southern Sierra Nevada regions during the later half of
the cold season. These regions coincide with the areas in which the
largest reduction in the surface albedo is projected (Fig. 4). Thus, the
large warming signals in these regions are, at least partially, related
with the reduction in winter snowcover that resulted in increases in the
surface solar forcing. In the coastal regions, warming over the northern
Coastal Range is larger than over the southern Coastal Range for both
fall and winter. These warming signals in the coastal regions may be
related with the large-scale warming signals that generally increase
towards the north as can be inferred from the temperature change signals
over the eastern Pacific Ocean (Fig. 3). The reduction in the surface
albedo may also contribute to the projected warming signals in the
northern Coastal Range, especially during winter.

Table 2. The projected climate change signals in key surface hydrologic
variables. The numbers in the parenthesis indicate the percent of the
late 20th century RCM climatology. The percent change in snowfall and
snowmelt in the southern Coastal Range region (SC) is undefined due to
very small values in both the control and mid-century periods.

  ---------- --------- ---------- ---------- ---------- ---------- ----------
             Season    NC         SC         SH         NS         SS

  Precip     Fall      22.5       -6.6       23.5       16.1       -16.0
                       (11.5)     (-11.7)    (15.2)     (9.85)     (-15.4)

             Winter    -64.4      -15.1      -44.8      -82.6      -39.8
                       (-21.5)    (-14.6)    (-17.1)    (-26.6)    (-20.9)

             Oct-Mar   -21.0      -10.9      -10.7      -33.2      -27.9
                       (-8.46)    (-13.6)    (-5.12)    (-14.0)    (-19.0)

  Rainfall   Fall      25.4       -6.7       34.8       29.6       -3.6
                       (13.5)     (-12.2)    (28.0)     (22.7)     (-5.1)

             Winter    -54.7      -15.5      -14.0      -45.8      -12.2
                       (-19.4)    (-15.0)    (-6.93)    (-19.1)    (-10.7)

             Oct-Mar   -14.6      -11.2      10.4 (6.4) -8.1       -7.9
                       (-6.23)    (-14.0)               (-4.4)     (-8.6)

  Snowfall   Fall      -2.9       0.2 (n/a)  -11.3      -13.5      -12.5
                       (-41.7)               (-38.0)    (-40.5)    (-36.5)

             Winter    -9.7       0.4 (n/a)  -30.8      -36.8      -27.6
                       (-53.1)               (-51.3)    (-52.6)    (-36.5)

             Oct-Mar   -6.3       0.3 (na/a) -21.1      -25.1      -20.0
                       (-50.0)               (-46.9)    (-48.7)    (-36.5)

  Runoff     Fall      -0.1       -0.2       0.7 (5.6)  -1.9       -6.5
                       (-0.4)     (-11.7)               (-10.7)    (-63.1)

             Winter    -12.9      -3.4       -3.6       -24.9      -16.5
                       (-10.4)    (-28.2)    (-3.8)     (-22.6)    (-29.4)

             Oct-Mar   -6.5       -1.78      -1.4       -13.4      -11.5
                       (-8.6)     (-26.7)    (-2.7)     (-21.0)    (-34.6)

  Snowmelt   Fall      -2.89      0.2 (n/a)  -10.1      -11.3      -8.5
                       (-42.6)               (-36.4)    (-37.7)    (-29.9)

             Winter    -9.75      0.4 (n/a)  -32.3      -39.4      -30.7
                       (-52.8)               (-51.9)    (-54.0)    (-38.6)

             Oct-Mar   -6.32      0.3 (n/a)  -21.2      -25.4      -19.6
                       (-50.0)               (-47.2)    (-49.2)    (-36.3)

  SWE        Fall      0.1 (42.3) 0.0 (0.0)  -1.1       -1.4       -3.1
                                             (-32.9)    (-29.9)    (-42.7)

             Winter    -1.3       0.0 (0.0)  -2.9       -5.0       -13.2
                       (-78.5)               (-58.1)    (-65.5)    (-67.9)

             Oct-Mar   -0.6       0.0 (0.0)  -2.0       -3.21      -8.2
                       (-60.8)               (-47.7)    (-52.0)    (-61.1)

  T2         Fall      0.87       0.59       0.95       0.98       1.38

             Winter    1.73       1.42       1.77       1.94       2.09

             Oct-Mar   1.30       1.00       1.36       1.46       1.74
  ---------- --------- ---------- ---------- ---------- ---------- ----------

4\. Precipitation changes

The cold season precipitation decreases in almost all regions in
California in the warmer climate (Fig. 5). The decrease in precipitation
is most pronounced in the southern Coastal Range, the Sierra Nevada, and
the southern California regions by 10-25% of the amounts in the late
20th century climate run. The significant decrease in cold season
precipitation in the Sierra Nevada region is a serious concern because
of its importance in California water resources. The spatial pattern of
the precipitation change signals varies significantly between the early
and late half of the cold season, especially in the north-south
direction. In fall, the precipitation increases in the northern
California region are accompanied by the decreases in the southern
California region (Fig. 5b). This spatial pattern in the fall
precipitation change signals is reversed in winter; positive (negative)
precipitation changes in the southern (northern) California region (Fig.
5c). The statistical significance of the precipitation change signals is
lower than that of the low-level temperature changes similarly in
previous studies (IPCC 2005, 2007). The statistical significance of the
positive seasonal precipitation signals is especially low. The highest
statistical significance of the seasonal precipitation signals occurs in
high elevation regions, over the southern Sierra Nevada region in fall
and the northern Coastal Range and the northern Sierra Nevada regions in
winter where the statistical significance exceeds the 90% level.

![](media/image5.png){width="5.1in" height="2.55in"}

Figure 5. The climate change signal in precipitation (percent of the
control climate) for (a) the entire cold season (October-March), (b)
fall (OND) and winter (JFM).

The differences in rainfall and snowfall between the late 20th century
and the mid-21st century are further examined below. The results show
that the cold season rainfall decreases generally in California except
in high elevation regions in the Sierra Nevada where the projected
rainfall increases are as large as 25% of the values in the late 20th
century climate condition (Fig. 6). The corresponding statistical
significance is similar to that of the precipitation change signals. The
largest decrease in cold season rainfall occurs in the southern Coastal
Range, the Central Valley, and the southern California regions by 10-25%
of the values in the late 20th century run. Seasonally, the spatial
pattern of the projected rainfall changes in California closely
resembles the seasonal precipitation changes. Important differences
between the seasonal precipitation and rainfall changes appear in the
northern Sierra Nevada region during fall; fall rainfall (Fig. 6b)
increases in the region despite the decrease in precipitation (Fig. 5b).
This is because the reduction in fall snowfall is much larger than the
increase in rainfall in this region.

![](media/image6.png){width="5.1in" height="2.55in"}

Figure 6. Same as Figure 5, but for the seasonal rainfall changes.

The projected mid-21st century snowfall decreases by 25-50% of the late
20th century values in the Sierra Nevada region and by over 50% in the
Mt. Shasta region (Fig. 7). This is one of important consequences of the
low tropospheric warming which results in higher freezing level
altitudes during storms (Giorgi et al. 1997; Kim 2001). The snowfall
over the Sierra Nevada decreases by similar percentages for both fall
and winter; however, the snowfall decreases in the Mt. Shasta region are
much larger in winter than in fall (not shown). The statistical
significance of the projected snowfall change signals exceeds the 95%
level in the northern Coastal Range, the Mt. Shasta and the Sierra
Nevada regions where significant snowfall occurs.

![](media/image7.png){width="5.1in" height="2.55in"}

Figure 7. Same as Figure 5, but for the seasonal snowfall changes.

The climate change signals in the seasonal precipitation, rainfall, and
snowfall in the 5 California sub-regions are also summarized in Table 2.
Precipitation and rainfall increases during fall in the three northern
regions, the northern Coastal Range, Mt. Shasta, and the northern Sierra
Nevada. The increase in the fall precipitation and rainfall in these
regions are followed by decreases during the winter, resulting in net
decreases in precipitation and rainfall over the entire cold season.
Note that Figures 5-7 present the climate change signals in terms of the
percentage of the amounts in the control climate. Because precipitation
amounts are much larger in winter than in fall (not shown), the
precipitation changes over the entire cold season are dominated by the
changes in winter. In the two southern regions, the southern Coastal
Range and the southern Sierra Nevada, precipitation and rainfall
decreases for both fall and winter. Snowfall decreases in all regions
except in the southern Coastal Range region where snowfall is
insignificant.

5\. The changes in the seasonal snowpack and snowmelt

The projected seasonal-mean snow water equivalent (SWE) decreases in the
high elevation regions in California (Fig. 8). The significant reduction
in SWE during winter is alarming because the amount of snowpack in high
elevation regions at the end of winter is a key indicator for warm
season water supply in California. The projected SWE decreases in the
three northern regions are about 30-40% in fall and almost 60-80% in
winter (Table 2). For the entire cold season, the SWE reduction is
almost as large as the amounts in the present-day condition. The
decrease in SWE is mainly due to the decrease in snowfall and may be
augmented by increased melting due to warmer low-level temperature. The
reduction in SWE for both seasons is consistent with the reduction of
the surface albedo in the mountainous regions in California as shown in
Fig. 4.

The snowmelt in the three sub-regions decreases throughout the cold
season in response to the reduced snowfall in the warmer climate (not
shown). The largest reduction occurs in the northern Sierra Nevada
region (Table 2) where the snowmelt decreases by 38% and 54% of the late
20th century values for fall and winter, respectively. The percent
change in the projected snowmelt reduction in the Mt. Shasta region is
similar to that in the northern Sierra Nevada region. In the southern
Sierra Nevada region, the amount of snowmelt changes remains somewhat
smaller than the amounts in the Mt. Shasta and the northern Sierra
Nevada regions for both fall and winter.

![](media/image8.png){width="5.1in" height="2.4in"}

Figure 8. The climate change signals (% of the control climate) in SWE
for (a) the entire cold season, (b) fall, and (c) winter.

6\. Runoff changes

The projected runoff decreases in all 5 sub-regions for both fall and
winter except in the Mt. Shasta region where runoff increases slightly
in fall in response to the slight increase in fall rainfall (Table 2).
In the 3 northern California regions (the northern Coastal Range, Mt.
Shasta, and the northern Sierra Nevada) runoff changes show large
seasonal variations with smaller decreases in fall and larger decreases
in winter. In these northern regions, the increase in fall precipitation
and rainfall partially compensates the decrease in fall snowfall to
result in relatively small amount of runoff reduction in fall. In the
two southern regions, the southern Coastal Range and the southern Sierra
Nevada, significant reduction in seasonal runoff is projected for the
both season in response to the decrease in precipitation throughout the
cold season. The amount of runoff changes is smallest in the Mt. Shasta
region and largest in the southern Sierra Nevada region (Table 2).

7\. Summary and conclusions

The impact of the global climate change induced by the increase in the
atmospheric GHG on the cold season surface hydroclimate in California
during the mid-20th century has been investigated using the dynamical
downscaling method. In the present study, the WRF model is driven by the
3-hourly large-scale atmospheric and SST forcing from a CCSM3 global
climate projection on the basis of the SRES-A1B emission scenarios to
obtain regional-scale climate data at a 36km horizontal resolution. The
cold season includes fall and winter in this study. The climate change
signals of key hydroclimate fields are calculated as the difference in
the 20-year climatology between 2035-2054 and 1961-1980.

The regional climate change signals obtained in this study show that;

\(1\) The low-level air temperature will increase by 1-2.5K, with larger
increases in high elevation regions during the late half of the cold
season. The geographical variations in the warming signals are
associated with the effects the significant depletion of snowpack in the
warmer climate and the prevailing westerlies.

\(2\) Surface albedo decreases notably in high elevation regions in
northern California and the Sierra Nevada. The decrease in the surface
albedo is more pronounced in winter than in fall because of larger
depletion of snowpack in winter.

\(3\) The cold season precipitation decreases in the entire region of
California. The precipitation changes show strong interseasonal
variations: Fall precipitation increases in the northern California and
decreases in the southern California region. The winter precipitation
changes show opposite features with increases (decreases) in the
southern (northern) California region.

\(4\) Winter rainfall changes are similar to those in precipitation.
Rainfall increases notably in the high elevation regions in the northern
Sierra Nevada where a significant portion of snowfall in the present-day
climate falls as rain in the warmer climate due to higher freezing level
altitudes.

\(5\) Snow fall decreases for all seasons by 25-50% of the amounts in
the present-day climate. The largest percent-decrease in snowfall occurs
in the Mt. Shasta and the northern Sierra Nevada regions during the
second half of the cold season (winter).

\(6\) The snowpack in the high elevation Mt. Shasta and the Sierra
Nevada regions decrease by over 40% in fall and nearly 70% in winter due
to reduced snowfall. The reduced snowfall in the warmer climate also
results in the reduction in snowmelt by 38% and 54% of the late 20th
century values during fall and winter, respectively.

\(7\) The cold season runoff decreases in California due to reduced
precipitation.

\(8\) The statistical significance of the projected climate change
signals is large for the low-level temperature and snowfall but is low
for precipitation and rainfall. Geographically, the statistical
significance in high elevation regions generally exceeds that in low
elevation regions.

The climate change signals obtained in this study suggests that the
climate change will adversely affect the water resources in California.
The projected decrease in snowfall and snowpack is of a special concern
because snowpack in high elevation regions plays a role of natural
reservoir that stores water during the wet cold season and gradually
release through the early part of the dry warm season. It must be noted
that the results presented in this study represent only one of many
scenarios that are equally plausible. The changes in the key surface
hydroclimate fields projected in this study compares qualitatively with
the results in previous studies (Leung and Ghan 1999; Kim et al. 2002);
however, details in the projected climate change signals vary among
these studies. Further examinations reveal that major differences in the
climate change signals projected in this and previous studies,
especially the changes in regional precipitation) are primarily due to
the differences in the GCM climate projections used in each regional
climate change study.

8\. Acknowledgements

This research has been supported by the JPL contracts 1312546 and
1288653 to the UCLA Joint Institute for Regional Earth System Sciences
and Engineering (JIFRESSE).

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