• Introduction
• Data and Methodology
• Results
• Discussion and Summary
• References
• Figures and Tables

FIGURES

• Figure 1
• Figure 2
• Figure 3
• Figure 4
• Figure 5
• Figure 6
• Figure 7
• Figure 8
• Figure 9
• Figure 10

Ý

Large Scale Meteorological Coupling is studied between the South America Total Cloud Cover and ENSO (El NiÒo Southern Oscillation) phenomena in its different phases (NiÒo, NiÒa and Normal) situation. Based on a Singular Value Decomposition (SVD) technique we compute the Heterogeneous Correlation Pattern for South America Region from 1980 to 1999. Clustering the same nature events we identify the teleconnection coherence zone and their influence regions for each types of events. Finally, for the last NiÒo Event (1997/1998) we compute the local incidence pattern in Buenos Aires where we operate a Lidar Station and Radiometry (34ƒ36'S, 58ƒ26'W) as a correlation between regional variables, affected by these Large Scale Coupling, and the local variables measured in Buenos Aires, Argentina.

1. Introduction

Large scale link between the interannual variations of ocean surface temperatures in the equatorial central and eastern Pacific regions to persistent regional and global atmospheric anomalies has been demonstrated after many scientific works in the last decade.

A large scale abnormal warming in the equatorial Pacific known as El NiÒo, refers to the large scale atmospheric effects related to the surface ocean warming. During the El NiÒo episodes lower than normal pressures are observed in the eastern tropical Pacific and higher pressures are found over western Pacific as Indonesia and northern Australia. These conditions characterize the warm phase of the Southern Oscillation (SO), which is often referred to as an El NiÒo Southern Oscillation (ENSO) episode.

During periods when ocean surface temperatures are colder (the cold phase of the SO, know as La NiÒa), lower than normal pressures are found over western Pacific region and higher pressures are observed over the eastern tropical Pacific.

During a warm episode winter, mid-latitude low pressure systems tend to be more strong than in normality in the the Gulf of Alaska region. These systems pump abnormally warm air into western Canada, Alaska and the extreme northern portion of the contiguous United States. Storms also tend to be more vigorous in the Gulf of Mexico and along the southeast coast of the United States resulting in wetter conditions than normal in that region.

During cold episodes, colder ocean temperatures in the equatorial central Pacific act to inhibit the formation of rain-producing clouds over that region. Wetter conditions are also observed over southeastern Africa and northern Brazil, during the northern winter season. Drier conditions during cold episodes are observed along the west coast of tropical South America, and at subtropical latitudes of North America (Gulf Coast) and South America (southern Brazil to central Argentina) during their respective winter seasons

During warm and cold episodes the normal pattern of tropical precipitation becomes altered affecting the tropical atmospheric circulation features. Also, during warm and cold episodes extratropical storms and frontal systems follow paths that are significantly different from normal, resulting in persistent temperature and precipitation anomalies in many different regions

The relation of that warm and cold episodes in the central Pacific with a highly precipitation anomalies persistence pattern in consistence with different episodes from latitudes corresponding to North America Wang H. et al. (1999), Barsugli et al. (1999), Bell et al. (1999), up to South America and specially from southern Brazil to the central Argentina Mechoso C. and Iribarren (1992), Lenters and Cook (1995), Harzallah et al (1996),Grimm et al. (2000), Ropelewski and Halpert (1987; 1989), Halpert and Ropelewski (1992).

Specifically a general description ENSO episode related with seasonal mechanism was found in Aceituno, P (1988), Tziperman et al(1997) and many others. Concerning to the upper-tropospheric circulation features that accompany extreme phases of the Southern Oscillation are discussed in the work of Arkin, 1982.

Evidence of ENSO teleconnection impacts over local parameters such precipitation and TCC in South America are demonstrated by:

- Pinker and Laszlo (1992), studied the variability of solar irradiance of Amazon basin.

- Piacentini R. (1998) quantifying the nebulosity fraction reduction in the region of Rio de la Plate basin including Buenos Aires.

- P.Ristori et al, 2000 ILRC 2000 over Bs. As. (34†36íS 58†26íW) region quantifying the temporal evolution of teleconnection coupling evolution in time during the last ENSO episodes (1997//1998).

- Grimm et al (2000); was detected and calculated the coherence rainfall response to the El NiÒo and La NiÒa events from 1957 to 1991.

- Mechoso et Iribarren (1992); was calculate the streamflow variability in Uruguay country from 1901 to 1989 and detecting the ENSO phases.

In this work we present a geographical "coherence zone" identification of the region having the major coupling variability driving by ENSO events in their different phases: NiÒo (+1), La NiÒa (-1), Normality (0) scrutiny from 1980 to 1999 period. Starting in section 2 with a description of data base used and the methodology utilized; in the section 3 we present the principal results for this application. Finally, with the objective to achieved the Air Quality implications we compute the local influence over total incoming visible radiation flux and their coupled variability over Mixed Layer Atmospheric Boundary Layer Height, as a local parameter, for the last strong ENSO event (1997//1998). Finally a summary and concluding remark are presented in section 4.

2. Data and Methodology

The El NiÒo region SST and South America TCC data for the large scale-to-regional study comes from the NCEP ñ NCAR CDAS Reanalysis database. Visible integrated incoming radiation temporal series from 0800 ST to 1200 ST and the Atmospheric Boundary Layer (ABL) structural parameter temporal series evolution used in the regional to local scale analysis comes from the CEILAP (CITEFA-CONICET) center placed in Villa Martelli, Buenos Aires, Argentina.

The methodology involved in the large scale teleconnection process between the El NiÒo 3 SST region and South America TCC is a Principal Components (PC) based Canonical Correlation Analysis (CCA) as presented in Bretheton et al., Barnet and Preisendorfer with further analysis over SST studies in Wallace et al.

In this case only a small but representative number of PC modes are retained to preserve the algorithm stability. CCA technique uses an intrinsic normalization of the cross corvariance matrix of the studied fields in the SVD analysis that translates the othonormality from the spatial to temporal field. In few words this means that the expansion coefficients (temporal series) of each mode of each field has the following properties: If a_k(t) is the expansion coefficient of the k^th TCC pattern and b_k(t) is the expansion coefficient of the k^th pattern, then the CCA technique assures that:

This choice was taken to achieve the geophysical goal of isolating the most significant Center Pacific SST natural oscillation from the anomaly induced by the El NiÒo Process an then, via the Heterogeneous correlation maps, detect coherent regions between this fields. CCA expansion coefficients, patterns, weight vectors and correlation maps were found for the 1960 - 2000 TCC and SST time series. Then the most important SST CCA expansion coefficients were correlated with the TCC to detect geographical coherence regions. This last correlation was implemented both with the total time series and for specific NiÒo, NiÒa and Normality periods. For this specific periods it was employed a 2 years timeframe.

CCA expansion coefficients, patterns, weight vectors and correlation maps were found for the 1960 - 2000 TCC and SST time series. Then the most important SST CCA expansion coefficients were correlated with the TCC to detect geographical coherence regions.

This last correlation was implemented both with the total time series and for specific NiÒo, NiÒa and Normality periods.

After demonstrating the impact over the South America TCC, 1996-1998 visible incoming radiation and ABL height time series were used to analyze the influence of this large scale variable over local field variables during the last Normality and El NiÒo events. In this case, correlation analysis was the selected tool to evidence the coupling between this set of variables.

3. Results

In our first phenomenological approach to detect the influence of the El NiÒo/La NiÒa events over the South America cloud cover the whole 1960 - 1980 period is analyzed. The PC based CCA analysis is implemented with the 5 more significative PC modes for each field. Results of this study can be seen in Figure 1 for the first tree modes. An important spatial correlation of the 80% was found between the third CCA expansion coefficient of the 1960-2000 and the El NiÒo 3 anomaly.

Previous studies (Ristori, Fochesatto et al., 2000) shows South America coherence regions for the Normality 1995-1996 period and for the last El NiÒo 1997-1998 period via SVD analysis. In this case we can see a sort of similarity between the first two CCA maps and the normality period maps and between the third CCA maps and the anomaly period map.

In a second approach, a clustering technique based in the correlation study for a given time frame identified by El NiÒo, Normality or La NiÒa, compare the SST CCA expansion coefficients calculated before and the South America TCC with results shown in Table 1.

CCA_5,n means the 'n' canonical correlation of the 5 PC modes retained in the CCA, r(a_k,b_k) in the temporal correlation between the most significative expansion coefficients, SCF is the squared covariance fraction between the true and the synthetic reconstructed covariance fraction for each mode and the CSCF is the correspondant cumulative covariance fraction taking into account the current as well as the previous calculated modes. Finally, for this table, the correspondent heterogeneous correlation maps are shown in figures 2 to 8.

After computing the large scale coupling, we proceed by a downscaling process to quantify the regional to local impact process between the most significant variables evolves in the air pollution process. For the large to regional scale studies (only for the 1996-1998 period in which local measurements had been made), scatter plots between the TCC and the Visible Radiation temporal series are shown with -52% for normality and -78% for anomaly periods (Figure 9).

Figure 10 shows the linear correlation between Visible Radiation an ABL height monthly mean with annual time lag.

In our first phenomenological approach to detect the influence of the El NiÒo/La NiÒa events over the South America cloud cover the whole 1960 - 1980 period was analyzed. Results of this study can be seen in Figure 1. An important spatial correlation of the 80% was found between the third CCA expansion coefficient of the 1960-2000 and the El NiÒo 3 anomaly.

Previous studies (Ristori, Fochesatto et al, 2000) shows South America coherence regions for the Normality 1995-1996 period and for the last El NiÒo 1997-1998 period via SVD analysis. In this case we can see a sort of similarity between the first two CCA maps and the normality period maps and between the third CCA maps and the anomaly period map.

In a second approach, a clustering technique based in the correlation study for a given timeframe identified by El NiÒo, Normality or La NiÒa, compare the SST CCA expansion coefficients calculated before and the South America TCC with results shown in Table 1. The correspondent heterogeneous correlation maps are shown in figures 2 to 8.

For the large to regional scale studies (only for the 1996-1998 period in which local measurements had been made), scatter plots between the TCC and the Visible Radiation temporal series is shown with -52% for normality and -78% for anomaly periods (Figure 9). Figure 10 shows the linear correlation between Visible Radiation an ABL height monthly mean with annual time lag.

4. Discussion and Summary

Utilizing these clustering by episodes was possible to derive geographic composite patterns from diferents TCC condition driving by different SST phases behavior.

As primary conclusion we observe systematic pattern in the +1 and -1 conditions over South America centered in the Rio de la Plata basin having a strong influence in the local parameters such as the ventilation coefficients affecting the Air Quality of Buenos Aires City.

The second one is a good agreement obtained with the rainfall studies if it's considered the SST-TTC teleconnection as a precursor mechanism of the rainfall impacts. In this case teleconnection pattern (SST - TCC) was observed to have approximately the same pattern to those obtained by Grim et al., 2000 in their rainfall ENSO study. In particular for the "El NiÒo 1982, 1986, 1991" and the "La NiÒa 1988" periods, we retrieve almost the same coherence zone detected in their composite precipitation patterns studies in the reference mentioned above. The coupling region cover the central part of the Rio de la Plata Basin and in particular the north-eastern of Uruguay and southern of Brazil as we see in our teleconnection figures 3,4,5.

For the regional variables comparison we observe significant inter-annual variation reflected over TCC, FV and ABL Height for the mean seasonal values SON and DJF showed in Table 2.

Finally, evidence of ENSO coupling in time was observed in Table 3 where was calculated the inter-seasonal variations percents making a direct comparison of the real to the expected (non-anomalies) values each one. As an example, we shown for the transition periods JJA to SON a ñ33% extracted from lidar data, when the expected seasonal variation was +37% corresponding to the moving values towards spring season. The same situation was observed for the SON to DJF with real -34% compared to the expected +20% corresponding to the seasonal change from the spring to the summer in response to the ENSO forcing.

5. References

Grimm et al, . 2000. Climate Variability in Southern South America Associated with El NiÒo and La NiÒa Events', J. of Climate, 13, 35-58.

Mechoso C. and Perez Iribarren G. 1992. Streamflow in Southeastern south America and the Southern Oscillation. J. of Climate,5. 1535- 1539.

Pinker R. and Laszlo I., 1992. Interannual Variability of Solar Irradiance over the Amazon Basin Including the 1982-83 El NiÒo Year. J. of Climate. 5. 1305-1314.

Wallace et al. 1992. Singular Value Decomposition of Wintertime Sea Surface Temperature and 500-mb Height Anomalies. J of Climate, 5. 561-576.

Halpert M. and Ropelewski C. 1992. Surface Temperature Associated with the Southern Oscillation. J. of Climate, 5. 577- 593.

Bretherton C. et al. 1992. An Intercomparison of Methods for Finding Coupled Patterns in Climate Data. J. of Climate. 5. 541-560.

Barsugli J. et al. 1999. The Effect of the 1997/98 El NiÒo on Individual Large-Scale Weather Events. Bull. Amer. Meteor. Soc., 80, 1399- 1411.

H. von Storch and A. Navarra. Analysis of Climate Variability. Springer Verlag. Berlin, 1995.

Tziperman et al. 1997. Mechanism of Seasonal ñ ENSO Interaction. J. Atmos. Sci., 54, 61-71.

Lenters J. and Cook K., 1995. J. of Climate, 8, 2988-3005.

Harzallah et al. 1996. Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation. Int. J. of Climatol., 16, 861-878.

Wang H et al. 1999. Prediction of Seasonal Mean United States Precipitation Based on El NiÒo Sea Surface Temperatures. Geophys. Res. Lett., 9, 1314-1344.

Bell G. et al. 1999. Climate Assessment for 1998. Bull. Amer. Meteor. Soc., 80, 1999- .

Piacentini R. Influencias del Evento El NiÒo 1997-1998 sobre las intensidades solares globales incidents sobre Rosario, Argentina. ASADES, 2. Nƒ 2, 1998.

Ropelewski and Halpert 1987.Global and Regional Scale Precipitation patterns associated with the El NiÒo/Southern Oscillation. Mon. Whea. Rev. 115, 1606-1626.

Ropelewski and Halpert 1989.Precipitation patterns associated with the high index phase of the Southern Oscillation. J. of Climate, 2, 268-284.

Aceituno P. 1988, On the functioning of the Southern Oscillation in the South America Sector. Mon. Wea. Rev. 116, 505-525.

Arkin, 1982. The Relationship Between Interannual Variability in the 200mb Tropical Wind Field and the Southern Oscillation. Mon. Wea. Rev., 110, 1393-1404.

P. Ristori et al. 2000, Evidence of ENSO teleconnection with tropospheric ABL Dynamic parameters. Proceedings of 19^th ILRC, France.

P. Ristori et al. 2000, ClimatologÌa de la capa lÌmite atmosfÈrica en Buenos Aires: Impacto de ENSO. Accepted for publications for Anales AFA 2000.

Fochesatto et al. 2000, A survey of ABL Dynamics in Buenos Aires: A climatological study. Proceedings of 19^th ILRC, France.

Ý

6. Figures and Tables

Table 1

Ý

To achieve the 1997/1998 ENSO impact from regional to local scale, inter-annual and inter-seasonal projection coefficients are calculated over the regional and local coupled geophysical variables. We specialized the computation for the inter-annual coefficient variation between 1997//1998 for the seasonal period SON (September-October-November) and DJF (December-January- February).

Inter-seasonal variations for transition JJA (June-July-August), SON and DJF seasonal periods from the second half of 1997 to the first season of 1998 was calculated to shown the inter-seasonal coupled evolution over projected normality values as pre-filtering the anomalies values.