Report: Sub-Set of the IPCC Models That Could Be Used For

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 csiro_mk3_0 inmcm3_0 miroc3_2_hires miroc3_2_medres 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 20C A1B A2 B1 8 May 13 12:34 cccma_cgcm3_1 192*96 20C A1B A2 B1 16 May 4 12:07 csiro_mk3_0 144*90 20C A1B A2 B1 8 May 13 13:01 gfdl_cm2_1 128*60 20C A1B // B1 24 May 6 10:11 iap_fgoals1_0_g 96*72 20C A1B A2 B1 8 May 13 15:48 ipsl_cm4 128*64 20C A1B A2 B1 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