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The linear correlation coefficients show that RegCM3 had
superior performance than CPTEC/COLA to reproduce the
inter-seasonal variability of precipitation (0.84 against 0.64)
and air temperature (0.90 against 0.30) in the NDE area.
This is associated to the correction by RegCM3 of the out of
phase seasonal values of the CPTEC/COLA forecasts
(Figure 2).
(a)
variability of seasonal rainfall similar to the analysis. For
air temperature, RegCM3 seasonal mean also shows high
correction with the analysis (0.89) and after the correction
of it systematic cold bias the efficiency coefficient
approximates of 1. This coefficient sensitize that RegCM3
(CPTEC/COLA) is better (worse) preditor of the mean
seasonal values of air temperature and rainfall than the
mean of observations in the period analysed.
5. Acknowledgments
The present study was supported by CNPq and FAPESP
(Grant #2001/13925-5). We thank the NCEP, CPC/NOAA
and ICTP for providing the data set and model.
Table 1 – Averages of the 27 quarter for the analysis
(CPC or NCEP) and RegCM3 and CPTEC/COLA
forecasts, coefficient of efficiency (E) and linear
correlation (r) for precipitation and air temperature. The
value in parenthesis is the E after bias correction.
| 2005 | 2006 | 2007 |
(b)
Precipitation Mean (mm/day) r E
CPC 2.6 - -
RegCM3 2.9 0.84 0.62
CPTEC/COLA 5.2
0.64 -1.86
Air Temperature Mean ( o C)
NCEP 25.4 - -
RegCM3 23.7
0.89 -2.27
(0.80)
CPTEC/COLA 25.2 0.30 -0.05
| 2005 | 2006 | 2007 |
Figure 2. Seasonal averages over NDE of precipitation
(a) and air temperature (b).
The efficiency coefficient (E) for RegCM3 is positive (0.62;
Table 1), what indicates that the model is better predictor of
the seasonal rainfall than the average (calculated for all the
27 seasons) of the analysis of the CPC. The systematic
negative bias of air temperature in RegCM3 forecasts
produces a negative E coefficient (Table 2). However, if this
bias is removed of the time series, the efficient coefficient
(E b ) increases to 0.8 indicating the superior forecast of
RegCM3 over the mean of observations. The CPTEC/COLA
presents negative E values for both precipitation and air
temperature (Table 1) and this is justified by the bias and out
phase seasonal values (Figure 2) found in these forecasts.
Comparatively, the efficiency coefficient indicates that
RegCM3 is better predictor of seasonal rainfall and air
temperature over the NDE than CPTEC/COLA model.
4. Conclusions
This study evaluated the seasonal climate forecasts on the
Northeast of Brazil using the RegCM3 nested in the
CPTEC/COLA AGCM. The 27 seasonal forecasts were
compared with analysis of the CPC (precipitation) and
NCEP re-analysis (air temperature). The most important
result is that RegCM3 correct simulates systematic out of
phase mean values of rainfall and air temperature that is
found in the CPTEC/COLA AGCM forecasts. This implied
that RegCM3 was better predictor of mean seasonal rainfall
than the mean of analysis with efficiency coefficient near 1
and temporal correlation of 0.84. This high correlation
indicates that RegCM3 reproduces the inter-season
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