Rainfall in Uruguay (30-35S, 54-58W; see Fig. 1) occurs during all 12 months of the year. The complex interaction of several rainfall mechanisms produces a wet climate with a "flat" annual cycle. This is the case especially in the southernpart of Uruguay, which is influenced by the Rmo de la Plata and the Atlantic Ocean. In the northern part, fall and spring average rainfall exceeds that of winter and summer (Pisciottano et al. 1994, 1997).

Various studies have confirmed a significant influence of ENSO on interannual rainfall variability in Uruguay, with a tendency for above normal rainfall during warm events in the Pacific Ocean, especially in November and December (Ropelewski and Halpert 1987; Aceituno 1988; Pisciottano et al. 1994, 1997; Diaz et al. 1998). Pisciottano et al. 1997 presented a forecast for a wetter than normal November-December period in 1997 in four regions covering Uruguay, with probabilities of above median precipitation ranging from 76% to 94%, depending on the region. These predicted positive anomalies were confirmed by the observed rainfall which hapenned to be the highest in the entire record for each of the four regions. For the four regions used in that forecast the regional precipitation totals for November-December 1997 were: 574 mm for the northwestern region (NW), 558 mm for the northeastern region (NE), 464 mm for the southwestern region (SW), and 391 mm for the southeastern region.

Diagnostic studies have also revealed, among other results, that there are highly significant positive precipitation anomalies from March through July of the years following an El Nino event in the northern part of Uruguay, and a weak tendency for wet anomalies in the southern maritime subregions of the country (Pisciottano et al. 1994).

For diagnostic studies and for results presented here, we use a long time series of monthly values of the "Index of Wright" (IW) of SST anomalies in the central tropical Pacific (°C X100; Wright 1989). This region is similar to Nino 3 but a long time series is available for diagnostic studies. Values from 1987 to 1994 were calculated by averaging NOAA monthly gridded SST data over the Wright region as described explained in Pisciottano et al, 1997. The latest IW monthly values (1995 to February 1998) were calculated via a linear regression with the Nino 3 time series. The values of the IW for the past recent months are shown in Table 1.

Table 1. Recent (Jul. 1997-Feb. 1998) values of the IW SST index of Wright (°C X100); last value is an average for Jan-Feb 1998.

Our precipitation data are monthly values (mm) from 13 rainfall stations in Uruguay (Fig. 1). The data come from the Direccisn Nacional de Meteorologma (DNM) -- Uruguay. For diagnostic and prediction purposes we have grouped the stations into the same four regions defined in Pisciottano et al 1997. For each region, we calculated a monthly regional precipitation value for each month in the common period spanned by the records of stations included in the respective region. There are no gaps for these periods, and no "filling-blanks" procedures were used. Time series for April-July are formed from the monthly values for each region.

We defined fixed equiprobable categories (quartiles) of the predicted variable. Changes in the probabilities given a specific climatic event (e.g. an ENSO event) are calculated for each category and used to form a probabilistic prediction. First the statistical distributional parameters (first quartile, median, and third quartile called qcl, mcl and Qcl respectively) for all years are determined for April-July regional precipitation. These statistics characterize the rainfall climatology (cl) of the respective region. In the absence of any climate-determining information, a value "around mcl" is expected and the interval (qcl, Qcl) has a large (50%) chance of containing the bserved value. In this case the "forecast" would be mcl and an "error bar" would be (qcl, Qcl).

To incorporate the knowledge provided by the ENSO-rainfall relationships, we compare the statistical parameters of the "whole population" (all the values of the April-July total precipitation through the years) with those of the "subpopulation" obtained by selecting only the April-July total precipitation values for the years whose January-February mean IW was higher than a "critical value", IWcr. In agreement with former studies, we find that in the so defined "subpopulation" there is a tendency for enhanced rainfall. We test this statistical tendency with a hypergeometric distribution using the frequencies of above and below median rainfall in the population versus the frequencies for the "subpopulation". We note a balance between the "intensity" of a required event (as prescribed by IWcr) and the statistical significance of the rainfall differences (in the sense of Ropelewski and Halpert 1987; Pisciottano et al. 1994; Cazes et al. 1994). A very large IWcr produces a small number of events, yielding a lower significance than a moderate IWcr. It is found that IWcr=90 results in close to the highest significance for the regions NW (87%) and NE (99.42%). The low value obtained for NW is explained by the fact that the record length for that region (66 years) is shorter than for NE (83 years). Additional studies using rainfall stations in the NW region with a longer record (80 years) yield similar significance values to that of the NE region. We decided to use the same stations as in Pisciottano et al.1997. The significance values for regions SW and SE are very low for IWcr=90. However, if one chooses a much lower value for IWcr the significance values are higher than 95%. These results are in agreement with the above described regional rainfall tendencies for the March-July period.

Using Iwcr=90, we calculate the statistical parameters (qw, mw and Qw) for April-July for the NW and NE regions for the "subpopulation" (Jan-Feb IW>90). The procedure is similar to that used by Ropelewski and Halpert (1996). The statistical parameters (qcl, mcl, Qcl) and (qw, mw, Qw) for NW and NE are shown in Fig. 2.

Table 2 illustrates the rainfall distribution shift associated with years having Jan-Feb IW>90 through frequencies of occurrence of each of the four quartiles for each of the four regions.

Table 2. Frequencies of occurrence of rainfall in each of the 4 quartiles of the climatological distribution, given a year having Jan-Feb IW>90, for the four regions in Uruguay.

These results enable us to "predict" the expected precipitation as the median of the "subpopulation" (mw) rather than the climatological median (mcl). The interval (qw, QW) from the subpopulation is the "error bar" of the prediction. This technique circumvents problems associated with the nonlinearities of the SST-rainfall relationships and skewness of the rainfall distributions, and has been used during the past several years to experimentally predict rainfall in Uruguay. For example, in 1996 and 1997, a version of this technique predicted rainfall in three regions of Uruguay for November 1996-February 1997 and for September-December 1997 reasonably well. These forecasts were used by rice growers for water resource management (Pisciottano and Diaz, 1997; Cabral and Pisciottano 1997).

Based on the current values of the Pacific SST anomalies (Table 1) and the distributional shifts discussed above, we issue the following rainfall predictions for the April-July 1998 period for regions NW and NE in Uruguay.

Region I-NW Uruguay: A value around 503 mm of rainfall is expected, with 50% chance of between 303 and 624 mm. The probabilities of rainfall in the 3rd and the 4th quartile of the climatological distribution are 25% and 50%, respectively; and of rainfall above the median (343 mm) is 75%.

Region II-NE Uruguay: Approximately 590 mm is expected, with 50% chance of between 441 and 671 mm. The climatological 3rd quartile and 4th quartile have probabilities of 38% and 46%, respectively; andof rainfall above the median (418 mm) is 84%.

In summary, a wetter than normal April-July period is expected this year in northern Uruguay with probabilities of above median precipitation being 75% and 84 % respectively. For rainfall in the southern regions of Uruguay the climatological values should be used as reference for "expected" or "predicted" values.

Cabral, A. and G. Pisciottano, 1997: Elementos para entender el fensmeno 'El Nino' y sus aplicaciones en la agricultura. Revista de la Asociacisn de Cultivadores de Arroz del Uruguay. Junio 1997, 32-42.

Cazes, G., J. L. Genta and G. Pisciottano, 1994: Generacisn de informacisn hidrolsgicamente relevante a partir de informacisn y diagnsstico climatico. Aplicacisn en Uruguay. Memorias XVI Congreso Latino-americano de Hidraulica, Santiago, Chile, 3, 121-127. Diaz, A., C. Studzinski and C. R. Mechoso, 1998: Relationships between precipitation anomalies in Uruguay and southern Brazil and sea surface temperature in the Pacific and Atlantic Oceans. Journal of Climate, 11, 251-271.

Pisciottano, G., G. Cazes and A. Diaz, September 1997: A statistical-empirical forecast of November-December 1997 precipitation in Uruguay Based on the ENSO state. CPC - Experimental Long-Lead Forecast Bulletin.

Pisciottano, G., A. Diaz, G. Cazes and C.R. Mechoso, 1994: El Nino-Southern Oscillation impact on rainfall in Uruguay. J. Climate, 7, 1286-1302.

Pisciottano, G. and A. Diaz, 1997: Diagnsstico y prediccisn climatica en Uruguay. Memorias del Taller "Variabilidad climatica interanual: mitodos de pronsstico e impactos asociados". Santiago, Chile.

Ropelewski, C.F., and M.S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillation. Mon. Wea. Rev., 115, 1606-1626.

Ropelewski, C.F., and M.S. Halpert, 1996: Quantifying Southern Oscillation-precipitation relationships. J. Climate, 9, 1043-1959.

Wright, P. 1989: Homogenized long-period Southern Oscillation Indices. Int. J. of Climatol., 9, 34-54.

Fig.1. The 13 rainfall stations used in this study and the 4 regions in Uruguay. Stations: 1 Artigas; 2 Salto; 3 Paysandu; 4 Rivera; 5 Tacuarembo; 6 Melo; 7 Colonia; 8 Mercedes; 9 Trinidad; 10 San Jose; 11 Treinta y Tres; 12 Rocha; 13 Montevideo. Regions: I-NW, Northwest; II-NE, Northeast; III-SW, Southwest; IV-SE, Southeast.

Fig. 2. a) Medians and quartiles of the distribution of precipitation for the period April-July, in the region I-Northwest, for all the cases (Climatology) and for the subpopulation of cases when the Wright index averaged in the previous January-February period exceeded the value of 90 (IW>90). The data record spans from 1931 to 1996. b) Same as a), for the region II-Northeast. The data record spans from 1914 to 1996.