Climate Prediction of Precipitation for the Nordeste Rainy
Season of MAM 2000
contributed by Iracema F.A.Cavalcanti, Jos A. Marengo, Helio Camargo,
Cristopher A.C.Castro, Marcos B.Sanches, and Gilvan O.Sampaio
Centro de Previsao de Tempo e Estudos Climaticos (CPTEC)Instituto de Pesquisas Espaciais (INPE) Brazil
Monthly to seasonal dynamic atmospheric prediction at CPTEC have been performed since January 1995. The model used for these predictions is the CPTEC version of the COLA AGCM which was derived from the NCEP model ( Kinter et al. 1988) and includes a sophisticated biosphere model (Xue et al. 1991). The horizontal resolution of the AGCM CPTEC/COLA is T62 and there are 28 levels in the vertical (Cavalcanti et al. 1995). The seasonal predictions at CPTEC, during the first 3 years, were results of an ensemble of 4 members, using 4 consecutive days as initial conditions. In 1998 there was an increase in the number of ensemble members, with the prediction based on 25 integrations.
The application of boundary conditions also changed, from the use of persisted SST anomalies, to predicted SST. In the tropical Pacific, the SST is given by NCEP coupled model forecast, and in the tropical Atlantic, the SST is predicted using a statistical model (Pezzi et al. 1998). Outside these regions persisted SST anomalies are used.
Predictions for the rainy season of Nordeste (Northeast of Brazil) in 1995 were discussed in Nobre et al. (1995), and those for 1996, in Nobre and Cavalcanti (1996). Results from simulations (with a T42L18 version of the model) of the Nordeste rainy season of 1993 and 1994 using observed monthly Sea Surface Temperature (SST) as boundary conditions and T42L18 compared well with observed values of precipitation, and with NCEP reanalyses data (Cavalcanti et al. 1996). Precipitation anomalies in Nordeste (area averaged 20S-120S; 450W-350W) from a simulation of 11 years (1986 to 1996), using T42L18 reproduces much of the interannual variability in this region, (Cavalcanti et al. 1998). The forecast of the March-May 1998 and 1999 rainy season in Nordeste verified well.
Two sets of integrations were performed in the beginning of March 2000 for the seasonal prediction of the rainy season of Nordeste (MAM). The first set (I) was a result of 25 integrations using initial conditions of December, with predicted SST in the Tropical Pacific Ocean (NCEP) and Atlantic Ocean (SIMOC), and February persisted SST elsewhere. The model climatology is the climatology of 10 years from an ensemble of nine integrations. The second set (II) was performed with the same initial conditions but with persisted SST anomalies of February in all oceans.
Fig. 1a shows the ensemble mean of set (I) for the seasonal (MAM) average. Positive anomalies are predicted for the northwest of Nordeste region, associated with the influence of the ITCZ in that area. Negative anomalies are seen in the extreme eastern side of the Nordeste region. Accumulated observed precipitation reveals low rainfall amounts for the first 12 days of March in the eastern Nordeste and high amounts in the northwest side and areas of the interior. Ensemble mean of set (II) is shown in Fig. 1b. The position of ITCZ is similar to the result of set (I), establishing wet conditions in the northwest area of Nordeste. In this case, the interior and south of Nordeste indicates positive anomalies and only the extreme northeast of the region shows normal conditions. Above normal precipitation in the south of Nordeste extends to the Atlantic Ocean (which is not predicted by set (I) ) is a response of the model to positive SST anomalies in that region in February. Fig.2 shows the behaviour of individual members in north Nordeste. The spread when using the predicted SST fields is higher than when using the persisted SST anomalies, but the ensemble mean anomaly of MAM is positive in the two cases. Differences arise after May.
Verification of DJF 1999/2000 prediction is given in Fig.3a,b,c. Lower than normal precipitation in the western Amazonia and higher than normal in the eastern Amazonia and parts of Nordeste were well predicted by the model.
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