Report: Sub-set of IPCC models that could be used for
statistically downscaling the climate over California.
Celine Bonfils, Philip B. Duffy
June 23, 2005
I. Introduction:
This report aims to determine a possible sub-set of models that could be used, through
statistical downscaling methods, to estimate future changes in climate over California (CA).
Assessing the ability of the models to simulate the major features of today's climate has been
the goal of different intercomparison projects (AMIP, CMIP), and still remains a complex task.
An accurate simulation of current climate for several variables is an important benchmark but
does not guarantee that 1) the simulation is accurate for the right reasons (different combination
of forcings and feedbacks could lead to similar patterns); 2)other variables are similarly well
simulated; and 3) a model will simulate climate changes correctly.
In this report, we have used different criterions to provide some insights into the 22 IPCC
models characteristics and their ability to simulate the present-day Californian climate. The
criterions are based on the 1) availability of daily data (commonly necessary for climate impact
studies at regional scale); 2) availability of different future scenarios (SRESA1B, SRESA2,
SRESB1); 3) evaluation of the model performance over California based on observed
temperature and precipitation (biases and trends); 4) wish to obtain a large range of projected
changes in precipitation for the future climate. The resolution of the models has also been used
as a criterion of selection. This work is based on the models produced for the IPCC Fourth
Assessment Reoprt and, more specifically, on their ‘run1’ experiments found in the output
simulation dataset on June 23, 2005.
II. Results
II. 1. Availability in daily data
Among the 22 IPCC models available, only 14 models (Table 1) provide files of daily data
of temperature (T), precipitation (Pr), as well as minimum and maximum temperatures (Tmin
and Tmax, respectively). Only 6 of them offer also a monthly temporal resolution for minimum
and maximum temperatures (Table 2).
Table 1: Models offering daily data of T, Pr, Tmax, Tmin:
Resolution
Exp. Availability
Date Availability
Model
96*48
20C /// A2 B1
8 Jun 15 17:39
bccr_bcm2_0
128*64 20C A1B A2 B1
8 May 13 12:34 cccma_cgcm3_1
128*64 20C A1B A2 B1
8 May 24 17:35 cnrm_cm3
192*96 20C A1B A2 B1
16 May 4 12:07 csiro_mk3_0
144*90 20C A1B A2 B1
8 May 13 12:42 gfdl_cm2_0
144*90 20C A1B A2 B1
8 May 13 13:01 gfdl_cm2_1
72*46
20C /// /// ///
8 May 13 13:22
giss_model_e_h
72*46
20C A1B A2 B1
8 May 13 15:25 giss_model_e_r
128*60 20C A1B /// B1
24 May 6 10:11 iap_fgoals1_0_g
72*45
20C A1B A2 B1
8 May 13 15:40 inmcm3_0
96*72
20C A1B A2 B1
8 May 13 15:48
ipsl_cm4
320*160 20C A1B /// B1
8 May 24 21:08 miroc3_2_hires
128*64 20C A1B A2 B1
8 May 24 22:08 miroc3_2_medres
128*64 20C A1B A2 B1 32 May 26 17:03 ncar_pcm1
20C: 20th century; A1B: sresa1b; A2: sresa2; B1: sresb1; ///: missing
Note: Daily data of T, Tmin and Tmax (but not Pr) are also available for the model mri_cgcm2_3_2a. Daily data
of Pr and T (but not Tmin, Tmax) are available for the models mpi_echam5 and ncar_ccsm3_0. Finally, daily data
of T alone are also available for the model giss_aom.
Table 2: Models providing monthly data for Tmin and Tmax
bccr_bcm2_0
inmcm3_0
miroc3_2_medres
csiro_mk3_0
miroc3_2_hires
ncar_pcm1
II.2. Availability of sresa1ab future experiments
Among the 14 remaining models, three models have been rejected for data availability
issue: The model giss_model_e_h does not offer any daily data for the different SRES
experiments (Table 1). The model bccr_bcm2_0 does not provide the SRESA1B daily data and
the model miroc3_2_medres (in addition of overestimating precipitation during summer
months) does not provide data for the SRESA1B 'run1'.
II.3. Bias over California
The comparison of the simulated and observed climatology in precipitation and temperature
for the present-day climate (1950-1999) allows emphasizing models displaying strong bias over
California. The climatologies of the models are computed using monthly precipitation and
temperature from the 20c3m 'run1' experiments. Five models display strong bias over CA (Figs
1a-b):
- giss_model_e_r simulates too dry and too cold winters.
- cnrm_cm3 simulates a too dry climate during the last months of the year.
- gfdl_cm2_0 simulates too hot in summers.
- inmcm3_0 has a negative temperature bias all year round.
- miroc3_2_hires simulates too wet summers.
In addition, SRESAB1 monthly data of gfdl_cm2_0 are only provided from 2201 to 2300, and
there is no SRESAB1 monthly precipitation data available for miroc3_2_hires, preventing us to
complete the next analysis for these two models.
Fig 1. Climatological temperature and precipitation over CA (1950-1999). Observations are provided by the
University of Washington.
Eventually, only six models do not show such strong bias (Figs. 1c-d). These models are (short
list):
128*64
192*96
144*90
128*60
96*72
128*64
20C A1B A2 B1
20C A1B A2 B1
20C A1B A2 B1
20C A1B // B1
20C A1B A2 B1
20C A1B A2 B1
8 May 13 12:34 cccma_cgcm3_1
16 May 4 12:07 csiro_mk3_0
8 May 13 13:01 gfdl_cm2_1
24 May 6 10:11
iap_fgoals1_0_g
8 May 13 15:48
ipsl_cm4
32 May 26 17:03 ncar_pcm1
II.4. Precipitation response for the future climate (based on sresa1b experiment)
A decrease in precipitation is predicted by the models iap and gfdl, while the precipitation
rates do not strongly change in the future according to the model pcm1. Three models (ipsl,
csiro and cccma) simulate a wetter climate in the future, when compared to the 20th century
climate (Fig. 2). Only one of these three models should be kept.
- cccma: In comparison with the five other models remaining in the short list, the model cccma
simulates too cold winters and too hot summers for the 20th century. Its positive trend in annual
temperature for the 20th century is too strong while its trend in winter precipitation fits well the
observed one (not shown). The model cccma has a coarse resolution but more data are usually
available in T63 resolution (128  64), except for SRESA1B experiment.
Fig. 2: Simulated precipitation change (2050-2099) climatology minus (1950-1999) climatology.
- ipsl: This model has the coarsest resolution (96  72) compared to the other five models. It
also simulates too wet winter over CA and its projected increase in preciptation is the largest
over California (Fig 2). Its temperature and precipitation trends over CA (not shown) are
reasonably simulated for the 20th century.
- csiro: The model has a fine resolution (192  96). It reproduces well the observed
temperatures, as well as the 20th century trend in temperature. It shows a small positive
precipitation bias and a positive trend in winter precipitation that overestimates the observed
one.
Regarding the three last models, it has been observed that:
- Iap: The model shows too strong of a positive trend in annual temperature for the 20th
century, but its winter precipitation is reasonable when compared to observations. This model
simulates a drier climate in the future, and its climatologies in precipitation and temperature fit
well the observed one over CA.
- gfdl and pcm1: both models have a fine resolution (144  90 and 128  64, respectively),
simulate an accurate trend in annual temperature for the 20th century, and a positive trend in
winter precipitation that is slightly too Northward extended, when compared to observations.
These two models do not present particular bias for the present-day climate, except that the
model gfdl simulates slightly too cold, too wet winters. One could also raise a concern about
the peak of precipitation simulated in February by model pcm1 that does not appear in the
observations.
III. Conclusion:
While any assessment and ranking of models (including this report) should be treated very
carefully, the criterions that we have chosen have helped us to select few models that could be
used for downscaling climate over California. In order to select a large range of projected
changes in precipitation (an increase, a decrease and no change), one might consider the use of
the models csiro_mk3_0 (Australia), gfdl_cm2_1 (USA) and ncar_pcm1 (USA), that represent
well the seasonal patterns of temperature and precipitation over Californa. The models
iap_fgoals1_0_g (China) and ipsl_cm4 (France) could also be good alternative models to
achieve this task. Since this analyses have been performed only on a small area of the world,
additionnal analyses, such as simple correlation patterns plots, should be analyze to assess the
performance of these models on a global scale.
With Best Regards,
Céline Bonfils