Assessment of climate change model performance

Một phần của tài liệu Mekong River Basin Water Resources Assessment: Impacts of Climate Change doc (Trang 117 - 124)

11.1. Global climate change model selection

11.1.1. Assessment of climate change model performance

Figures 11.1 to 11.4 show pattern correlation coefficients and root mean square errors for

simulations represented the temporal and spatial pattern of monthly temperature of the Mekong catchments well, with pattern correlations of 0.92 or greater (Figures 1.1 and 1.2).

However the magnitude of temperature was less well represented, with RMS errors greater than 2.0 for the majority of models in some months (Figures 1.1 and 1.2).

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0 a) January

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

b) February

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

c) March

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

d) April

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

e) May

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

f) June

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

Figure 11.1. Pattern correlation and RMS error for observed versus simulated monthly temperature for January to June

g) July

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

h) August

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

i) September

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

j) October

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

k) November

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

l) December

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0

Figure 11.2. Pattern correlation and RMS error for observed versus simulated monthly temperature for July to December

Similarly rainfall magnitudes were poorly represented by the majority of models in some months with RMS error > 2.0 for most models (Figures 1.3 and 1.4). The temporal and spatial pattern of monthly precipitation was also less well represented generally by the GCM simulations, as pattern correlations were low for the majority of models. Correlations were less than 0.6 for all models in the drier months of January, February, March and December, and less than 0.8 for the majority of models in each month.

Models were selected on their capacity to represent seasonal temperature and precipitation for wet (May to October) and dry (November to April) seasons (Figure 11.5 and 11.6). Both the pattern and magnitude of temperature was well represented by all models for May to October, and by most models for November to April (Figure 11.5). The spatial and temporal pattern of precipitation from November to April was poorly represented, with pattern

correlations less than 0.8 for all models. The spatial and temporal pattern of seasonal

models (ncar_ccsm3_0; miub_echo_g; micro3_2_medres; micro3_2_hires; inv_echam4;

giss_aom; csiro_mk3_0, cnrm_cm3, cccma_cgcm3_1_t63; cccma_cgcm3_1 and bccr_bcm2_0) were used to make climate changed projections described in this report.

a) January

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

b) February

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

c) March

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

d) April

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

e) May

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

f) June

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0

Figure 11.3. Pattern correlation and RMS error for observed versus simulated monthly precipitation for January to June.

g) July

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

h) August

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

i) September

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

j) October

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

k) November

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

l) December

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 2 4 6 8

RMS Error (mm/day)

Correlation

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0

Figure 11.4. Pattern correlation and RMS error for observed versus simulated monthly precipitation for July to December.

a) May to October

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

b) November to April

0.90 0.92 0.94 0.96 0.98 1.00

0 1 2 3 4

RMS Error oC

Correlation

0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.00

0.0 1.0 2.0

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0

Figure 11.5. Pattern correlation and RMS error for observed versus simulated

seasonal temperature for wet (May to October) and dry (November to April) seasons.

a) May to October

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4

RMS Error (mm/day)

Correlation

b) November to April

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4

RMS Error (mm/day)

Correlation

ukmo_hadgem1 ukmo_hadcm3 ncar_pcm1 ncar_ccsm3_0 mri_cgcm2_3_2a mpi_echam5 miub_echo_g miroc3_2_medres miroc3_2_hires ipsl_cm4 inmcm3_0 ingv_echam4 iap_fgoals1_0_g giss_model_e_r giss_model_e_h giss_aom gfdl_cm2_1 gfdl_cm2_0 csiro_mk3_5 csiro_mk3_0 cnrm_cm3

cccma_cgcm3_1_t63 cccma_cgcm3_1 bccr_bcm2_0

Figure 11.6. Pattern correlation and RMS error for observed versus simulated

seasonal precipitation for wet (May to October) and dry (November to April) seasons.

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