Surface Circulation Types and Daily Maximum and Minimum Temperatures in Southern La Plata Basin

Transcription

1 2450 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y VOLUME 52 Surface Circulation Types and Daily Maximum and Minimum Temperatures in Southern La Plata Basin OLGA CLORINDA PENALBA Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina MARÍA LAURA BETTOLLI Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, and Consejo Nacional de Investigaciones Científicas y Tecnicas, Buenos Aires, Argentina PABLO ANDRÉS KRIEGER Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina (Manuscript received 29 January 2013, in final form 10 June 2013) ABSTRACT La Plata basin is one of the most important agricultural and hydropower-producing regions in the world. Extreme climate events such as cold and heat waves and frost events have a significant socioeconomic impact. This work analyzes the influence of the surface circulation in southern South America on daily maximum temperature T MAX and daily minimum temperature T MIN in southern La Plata basin. A Z test for the comparison of mean values and a Kolmogorov Smirnov test for the comparison of distributions of T MAX and T MIN associated with each circulation pattern were performed. Specific daily surface circulation types are found to contribute to T MAX and T MIN anomalies and to have a predominant occurrence in the development of the extreme temperature events in the region. The T MAX spatial response to the regional low-level circulation is more homogenous and extended than is the response of T MIN. 1. Introduction La Plata basin in southeastern South America (Fig. 1) is the second most important basin of the continent after the Amazon basin. Its morphologic and climatic variety has generated a diversity of interests related to its hydrological resources. The central Pampas, the most important region of agricultural production in Argentina (Fig. 1), is extending itself toward the south of the basin. Because of their impact on human activities, daily maximum and minimum temperatures are key variables Corresponding author address: Marıa Laura Bettolli, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires/Consejo Nacional de Investigaciones Cientıficas y Tecnicas (CONICET), Intendente G uiraldes 2160, Pabellon 2, Piso 2 Cuidad Universitaria, C1428EGA Buenos Aires, Argentina. bettolli@at.fcen.uba.ar in climate studies. In La Plata basin, incursions of both polar and tropical air masses are favored along the eastern side of the Andes mountains. This meridional transport of air masses often generates favorable conditions for the occurrence of extreme temperature events (Seluchi and Marengo 2000). The influence of daily circulation on surface temperature in southern South America has been documented by many authors in terms of synoptic climatology. Classifications of daily circulation in southern South America and its relation to austral winter surface temperature in Argentina have been studied by Vera and Vigliarolo (2000), Vera et al. (2002), Solman and Menendez (2003), and Espinoza et al. (2013). They employed a circulationto-environment scheme, a scheme in which the classification of circulation data is independent of the environmental response (Yarnal and Draves 1993). The relation between circulation and surface temperature can also be studied DOI: /JAMC-D Ó 2013 American Meteorological Society

2 NOVEMBER 2013 P E N A L B A E T A L FIG. 1. Region of study. Southern La Plata basin and the central Pampas region are indicated by the outer and inner rectangles, respectively, and the shaded area denotes La Plata basin. with an environment-to-circulation scheme (Yarnal and Draves 1993). With this scheme, the synoptic circulation associated with surface weather is studied, and it is generally applied with a focus on extreme events. This method has been used by Rusticucci and Vargas (1995), M uller et al. (2003), Escobar et al. (2004), Cerne et al. (2007), and M uller and Berri (2007), among others, to study cold and heat waves and frost events. In previous work, Penalba and Bettolli (2011) employed a circulation-to-environment scheme to identify sea level pressure types over South America and to associate these with precipitation events of the central Pampas region during summer and winter. They identified specific patterns that favor episodes of daily precipitation with different intensities. In this paper, the linkage between circulation and surface variables is further studied. To this end, an analysis of the relation between the circulation patterns that were identified by Penalba and Bettolli (2011) and daily minimum and maximum temperatures in southern La Plata basin (SLPB; Fig. 1) is proposed. In addition, the degree of occurrence of these circulation patterns for extreme temperature events documented by other authors is evaluated. 2. Data and method The dominant sea level pressure circulation types (CT) that were found by Penalba and Bettolli (2011) are used in this paper (Figs. 2, 3). To define these CTs, the authors used daily sea level pressure (SLP) fields over southern South America (from 158 to 608S and from to 908W) from the National Centers for Environmental Prediction (NCEP) U.S. Department of Energy Atmospheric Model Intercomparison Project (AMIP)-II Reanalysis (R-2; Kanamitsu et al. 2002) for the reference period The daily fields were classified on the basis of a principal component analysis combined with a cluster analysis. The study concentrated on austral

3 2452 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y VOLUME 52 FIG. 2. Observed summer circulation types, their relationship with daily rainfall in the central Pampas region, and their properties. The dashed (solid) lines represent sea level pressure values that are lower (higher) than 1013 hpa. The contour interval is 2 hpa. Arrows illustrate vector wind at 1000 hpa. This figure is adapted from Penalba and Bettolli (2011).

4 NOVEMBER 2013 P E N A L B A E T A L FIG. 3. As in Fig. 2, but for winter. summer and winter (December February and June August, respectively). The classification resulted in five summer CTs (labeled as CTis, i 5 1 5) and seven wintercts(labeledasctiw, i 5 1 7). Details of the method are in Penalba and Bettolli (2011). The comparison with some of the extreme events documented by other authors required the utilization of daily SLP fields from outside the reference period In the case of events prior to 1979, fields from the NCEP National Center for Atmospheric Research global reanalysis (Kalnay et al. 1996) were used; for events after 1999, fields from R-2 (Kanamitsu et al. 2002) were used. Each one of these daily fields was assigned to the CT that correlated best with this field. For maximum temperatures T MAX and minimum temperatures T MIN, a gridded dataset generated by Tencer et al. (2011) was used for the reference period This dataset is based on observed daily data from meteorological stations in Argentina, Brazil, Paraguay, and Uruguay and covers SLPB with a resolution of 0.58 latitude longitude. For each CT, the mean values of T MAX and T MIN were calculated (i.e., a composite for each CT). The mean value was then compared with the mean value of all days except those classified within the given CT. This assures that the two involved samples are independent (Huth 2010). The comparison was evaluated using the Z test for a difference between two means under the null hypothesis that there is no difference between mean values (Wilks 1995). Since the sample sizes were sufficiently large in all cases, the Z statistic follows a Gaussian distribution (Wilks 1995). The rejection of the null hypothesis, with a confidence level of 99%, indicates that the temperature composite of a given CT is well separated from the composite of the rest of the data. The sign of the statistics indicates whether a particular CT favors the cold days (negative sign) or warm days (positive sign). In an analogous way, to compare quantitatively the empirical probability distribution function (pdf) of temperature (T MAX or T MIN ) conditioned to each CT with the pdf for the rest of the data, the Kolmogorov Smirnov (K-S) test was performed with a confidence level of 99% (Wilks 1995). The output from the K-S test istheabsolutevalueofthedifferencebetweenthetwo cumulative distribution functions, but the test does not provide information about the shape of the distributions. To visualize the effect of the CT on the distribution of T MAX and T MIN, observed daily data from five meteorological stations located in the central Pampas region, provided by the National Meteorological Service, were used. The areal mean was calculated, and the temperature distributions conditioned by each CT were plotted.

5 2454 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y VOLUME 52 FIG. 4.Z-test statistics for the summer season for (top) T MAX and (bottom) T MIN. The positive (negative) results that are statistically significant to the 99% level are shaded in orange (blue). 3. Results a. Circulation types and temperatures The daily temperature values are determined by fixed factors (e.g., latitude, altitude, vegetation, and soil type) and by variable factors (e.g., cloudiness and air and soil humidity). The atmospheric circulation conditions the variable factors through advection of properties (humidity and temperature) and through the radiation (cloudiness and air humidity). In this section, we analyze through the mean values and the distributions conditioned by each CT how the low-level circulation, represented by the CTs, affects the extreme daily temperatures. With the purpose of complementing these results, the daily rainfall related to each CT (Penalba and Bettolli 2011) is presented in Figs. 2 and 3 together with their spatial structure and principal characteristics. In sections 3a(1) and 3a(2), these and the statistical results from the Z and K-S tests are presented for summer and winter, respectively. 1) SUMMER For summer, the synoptic structure of CT1s favors a cold inflow to the region (Fig. 2), leading to significantly low T MAX and T MIN in almost the whole SLPB region (Z test; Fig. 4). The K-S results indicate that the distributions of both temperatures associated with CT1s are well separated from the rest of the days, with a notable shift to lower values (Fig. 5). Since CT1s also favors rainy days in the central Pampas region, the advective and radiative components combine to favor cold temperatures. The influence of CT4s is observed on both mean values and distributions of T MAX and T MIN in southern SLPB (Figs. 4, 5). CT4s shows an intensification and expansion of the southern Atlantic Ocean anticyclone, which favors stability at low levels and can be significantly associated with the dry days of the central Pampas region (Fig. 2). Clear skies and warm advection from the northeast, favored by CT4s, determine the high T MAX and T MIN daily values. CT5s is characterized by a warm northeastern flow and is related to significantly high temperatures, in the case of T MAX over almost the whole region and for T MIN to the south of the SLPB region (Fig. 4). Similar results are observed in the differences of the distributions through the K-S test (Fig. 5). CT5s is the most frequent summer pattern, with 31.5% of the studied cases (Fig. 2), and is also the pattern that is most similar to the summer mean SLP field. The effect of CT3s is principally noted in the low mean T MAX values and in the distribution of T MAX over almost the whole SLPB region (Figs. 4, 5). CT2s can be considered to have a neutral effect on daily extreme temperatures, since the effects of CT2s are confined to small areas on the periphery of SLPB. 2) WINTER For winter, CT1w affects mean value and distribution of both T MAX and T MIN, inducing significantly warmer temperatures in almost the entire SLPB region (Z and K-S tests; Figs. 6 and 7, respectively). The observed temperature distribution over the central Pampas region confirms these results, showing a shift toward warmer

6 NOVEMBER 2013 PENALBA ET AL FIG. 5. K-S test for (top) TMAX and (bottom) TMIN for the summer season. The statistically significant differences are shaded. In the inset plots, distributions of observed TMAX or TMIN over the central Pampas region for the days corresponding to each CT are displayed in red, and remaining days are in blue. For TMAX, the x axis runs from 15 to 45 in increments of 5 and the y axis runs from 0 to 0.25 in increments of 0.05; for TMIN, the x axis runs from 0 to 30 in increments of 5 and the y axis runs from 0 to 0.25 in increments of 0.05, except for CT2s and CT4s, for which it extends to TMAX and TMIN. CT1w is characterized by a cyclonic perturbation that dominates the circulation over the southern South Pacific Ocean which, combined with the high pressure over the Atlantic Ocean, favors the warm advection from the north and northeast (Fig. 3). This causes increased temperatures and generates distributions with significantly high mean values. CT4w and CT7w induce higher TMAX values over SLPB and southern SLPB, respectively. Both patterns favor dry days in the Pampas region, which generate stable low-level conditions related to a high pressure system that extends from the Atlantic Ocean to the center of the continent (Fig. 3). Clear skies and the northern/northeastern component of low-level winds lead to the warmer maximum temperatures associated with these two patterns. CT2w, CT5w, and CT6w induce significantly low mean values and differences of TMAX distributions. In the case of CT2w and CT5w, this is true over almost the whole region; for CT6w, it is only true over southern SLPB (Figs. 6, 7). These three patterns affect mean values and distributions of TMIN only to the south of SLPB. The low temperatures of the three patterns can be linked to the cold advection from the south/southeast. Since CT5w and CT6w also favor rainfall, lower radiation due to clouds is also a contributing factor (Fig. 3). The effects FIG. 6. As in Fig. 4, but for winter.

7 2456 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y VOLUME 52 FIG. 7. As in Fig. 5, but for winter. For T MAX, the x axis runs from 5 to 35 in increments of 5 and the y axis runs from 0 to 0.2 in increments of 0.02 for CT1w and CT3w; from 0 to 0.25 in increments of 0.05 for CT2w, CT6w, and CT7w; and from 0 to 0.35 in increments of 0.05 for CT5w. For T MIN, the x axis runs from 210 to 25 in increments of 5 and the y axis runs from 0 to 0.18 in increments of 0.02 for CT1w, CT2w, CT3w, and CT6w; from 0 to 0.2 in increments of 0.02 for CT4w and CT7w; and from 0 to 0.25 in increments of 0.05 for CT5w. of CT6w and CT7w on temperature are closely mirrored opposites. CT6w can be associated with a cold front that advances toward the northeast, with its postfrontal anticyclone-generating southern advection over southern SLPB while the warm air still remains over northeastern SLPB. CT7w instead shows the influence of the South Atlantic anticyclone that is positioned favoring a warm advection from the north-northeast over southern SLPB and an eastern component of the flow over northeastern SLPB. It is interesting to highlight that the spatial patterns of significant T MAX anomalies are more extended than those of T MIN, especially during winter. In general, T MIN anomalies are found in some subregions of the region of study, showing that local effects also condition the behavior of T MIN. b. Circulation types and temperature extreme events In this section we analyze whether the effects of the CTs on daily T MAX and T MIN are consistent with extreme temperature events that have previously been documented by other authors. The analyzed events correspond to heat and cold waves, cold surges, frosts, and snowfalls. For these events, the sequences and frequencies of the CTs defined in previous sections are presented in Tables 1 and 2, respectively. The dates and CTs in boldface indicate that the CT favors the thermal situation as found in the previous section. For this analysis, only events that affected widespread areas of the region were taken into account. The cold summer wave that took place from 4 to 12 February 1996 affected almost the whole of Argentina (Cerne and Rusticucci 1997). This wave is associated with seven consecutive days of the CT1s pattern, followed by one day of CT3s and CT5s (Table 1). CT1s induce significantly cold anomalies of T MAX and T MIN, and CT3s induces anomalies of T MAX (Figs. 4, 5). In particular, CT1s is the least frequent pattern of the season (7.1% of all cases) and is also one of the less persistent patterns, with 90% of the events in sequences of 1 3 days (Penalba and Bettolli 2011), which qualifies the event as rare. Another intense summer cold wave that affected large parts of the country occurred during 4 14 January 1971 (Rusticucci and Vargas 1995; Table 1). The sequence of patterns that dominated the cold wave was initiated by three days of CT5s, associated with the summer mean field of sea level pressure. Next was one day of CT2s, which is characterized by a perturbation over the continent and a weakening of the Atlantic anticyclone, related to a cold front affecting the region (Fig. 2). The following two days are dominated by CT1s, which represents a postfrontal anticyclone that moves forward over the continent, inducing an anomalous flow from the east-southeast over SLPB. This inflow of cold air was maintained by the persistence of the CT2s pattern during three consecutive days, and the situation was thereafter normalized with CT5s. The summer heat waves studied by Rusticucci and Vargas (1995), Cerne et al. (2007), and the Department of Atmospheric and Oceanographic Sciences of the University of Buenos Aires ( uba.ar/;banco/ola/) are characterized by predominant frequency and persistence of the CT4s and CT5s patterns (Table 1), inducing extremely hot temperatures that are well differentiated from the rest of the days (Figs. 4, 5). These patterns are also accompanied by CT2s, which represents a neutral effect on the temperature. It is important to highlight that CT4s is also related to dry

8 NOVEMBER 2013 P E N A L B A E T A L TABLE 1. Sequences of CTs that occurred during heat and cold waves. The CTs that favor the cold and hot anomalies of each event are highlighted in boldface. Event Year Sequences of CTs Summer Cold wave (Cerne and Rusticucci 1997) Feb 5 Feb 6 Feb 7 Feb 8 Feb 9 Feb 10 Feb 11 Feb 12 Feb CT1s CT1s CT1s CT1s CT1s CT1s CT1s CT3s CT5s Cold wave (Rusticucci and Vargas 1995) Jan 5 Jan 6 Jan 7 Jan 8 Jan 9 Jan CT5s CT5s CT5s CT2s CT1s CT1s 10 Jan 11 Jan 12 Jan 13 Jan 14 Jan CT2s CT2s CT2s CT5s CT5s Heat wave (Rusticucci and Vargas 1995) Jan 9 Jan 10 Jan 11 Jan 12 Jan CT2s CT2s CT5s CT5s CT5s Heat wave (Rusticucci and Vargas 1995) Jan 21 Jan 22 Jan 23 Jan 24 Jan 25 Jan CT2s CT2s CT5s CT4s CT5s CT5s 26 Jan 27 Jan 28 Jan 29 Jan 30 Jan 31 Jan CT2s CT2s CT2s CT4s CT4s CT5s Heat wave (Cerne et al. 2007) Jan 26 Jan 27 Jan 28 Jan 29 Jan 30 Jan 31 Jan 1 Feb 2 Feb CT5s CT4s CT4s CT4s CT5s CT5s CT5s CT5s CT5s Heat wave ( Jan 27 Jan 28 Jan 29 Jan 30 Jan 31 Jan 1 Feb CT5s CT4s CT4s CT5s CT3s CT3s CT3s Winter Cold wave (Rusticucci and Vargas 1995) Jul 14 Jul 15 Jul 16 Jul 17 Jul 18 Jul 19 Jul 20 Jul CT7w CT6w CT5w CT5w CT5w CT5w CT5w CT5w 21 Jul 22 Jul 23 Jul 24 Jul 25 Jul 26 Jul 27 Jul 28 Jul CT5w CT5w CT7w CT7w CT3w CT3w CT7w CT7w Cold wave (Rusticucci and Vargas 1995) Jul 6 Jul 7 Jul 8 Jul 9 Jul 10 Jul 11 Jul 12 Jul 13 Jul 14 Jul CT4w CT2w CT2w CT2w CT5w CT7w CT7w CT4w CT4w CT4w Heat wave (Rusticucci and Vargas 1995) Jul 23 Jul 24 Jul 25 Jul 26 Jul 27 Jul CT4w CT1w CT1w CT1w CT1w CT3w 28 Jul 29 Jul 30 Jul 31 Jul 1 Aug 2 Aug CT3w CT7w CT7w CT1w CT3w CT3w Heat wave ( Aug 22 Aug 23 Aug 24 Aug 25 Aug 26 Aug 27 Aug 28 Aug CT7w CT7w CT1w CT1w CT1w CT1w CT1w CT6w

9 2458 J O U R N A L O F A P P L I E D M E T E O R O L O G Y A N D C L I M A T O L O G Y VOLUME 52 TABLE 2. Frequencies of CT that occurred during cold surges, frosts, and snowfalls. The CTs that favor the cold anomalies of each event are highlighted in boldface. For the persistent generalized frosts, the frequency indicates the number of times that each CT started the event. Winter CT Frequency Cold surges (Escobar et al. 2004) CT2w 1 CT3w 1 CT5w 1 CT6w 2 Partial and generalized CT5w 4 frosts (M uller et al. 2003) CT6w 5 CT7w 2 Persistent generalized frosts CT2w 12 (M uller and Berri 2007) CT3w 1 CT4w 2 CT5w 6 CT6w 2 CT7w 7 Snowfalls (Salio et al. 2006) CT2w 8 CT3w 1 CT4w 2 CT5w 9 CT6w 11 CT7w 2 days (Fig. 2) and is the most persistent pattern of this season, with 19% of the events in sequences lasting from 4 to 7 days, and CT5s is the most frequent pattern, with 31.5% of the summer days (Penalba and Bettolli 2011). This situation indicates that the region has favorable conditions for the development of heat waves. The two winter heat waves analyzed here occurred from 22 July to 2 August 1979 (Rusticucci and Vargas 1995) and from 21 to 28 August 2002 ( at.fcen.uba.ar/;banco/ola/). Both show a high frequency of the patterns that induce higher temperatures: CT1w, CT4w, and CT7w (Table 1), in agreement with the previous section. Also, for both winter cold waves of Table 1, the predominant patterns that induce significantly lower temperatures are CT2w, CT5w, and CT6w. Of interest is that the cold wave that occurred during July 1973 developed a sequence of eight consecutive days of CT5w pattern. It is interesting to note that this CT is the least persistent pattern of the season, with 93.7% of the events in sequences of 1 3 days and is the least frequent one (6.9%; Penalba and Bettolli 2011). The cold winter outbreaks in southern South America were characterized by Escobar et al. (2004) (Table 2). Out of five types identified by the authors, four correspond to CT2w (one case), CT5w (one case), and CT6w (two cases), consistent with the findings in the previous section. Frost is an event that has a particularly negative impact on farmland. M uller et al. (2003) studied the circulation associated with days with partial or generalized frost events in the Pampas region. Of the 11 types of frost analyzed in detail by the authors, nine correspond to patterns CT5w (four cases) and CT6w (five cases) (Table 2), which are two patterns that induce low temperatures in SLPB (Figs. 6, 7). In a later work, M uller and Berri (2007) studied the atmospheric circulation patterns related to a persistent generalized frost event over the region. Out of 30 events studied by the authors, 20 involved the types CT2w, CT5w, and CT6w during their evolution (Table 2). Moreover, 12 events started with CT2w, 6 started with CT5w, and 2 started with CT6w (Table 2), which represent anticyclonic disturbances that break into South America, generating southerly wind anomalies and cold-air advection (Fig. 3). Occurrence of snowfall in southern SLPB was also considered. Snowfall on the coast of the province of Buenos Aires, south of SLPB, is a phenomenon that occurs sporadically. Salio et al. (2006) analyzed these snowfall events over a period of 35 years ( ) and found 38 events, of which 33 coincided with the months analyzed in this research. Comparing these days with the CT of this study, it was found that 28 days occurred in CT2w (8 cases), CT5w (9 cases), and CT6w (11 cases). In general, snowfall is associated with incursions of air masses of polar or Antarctic origin that reach subtropical latitudes (Salio et al. 2006) and is favored by the patterns found here. 4. Conclusions A study of maximum and minimum temperatures conditioned by observed surface circulation in SLPB was performed. This analysis was carried out through a test for the comparison of mean values and a nonparametric test for the comparison of distributions of maximum and minimum temperatures associated with each circulation pattern. To complement the analysis, the relation between the circulation patterns and daily rainfall over the region, studied by Penalba and Bettolli (2011), was integrated with the results. The results indicate that specific daily circulation patterns can be identified as responsible for a significant contribution to the maximum and minimum temperature anomalies. The different circulation types induce significantly different mean values and distribution of T MAX and T MIN, which are consistent with their effect on daily precipitation in the region. The T MAX spatial response to the regional low-level circulation is more homogenous and extended than the response of T MIN. This could be because T MIN is more affected by local

10 NOVEMBER 2013 P E N A L B A E T A L factors (wind, humidity, type of soil, cloudiness, etc.) than is T MAX. The degree of occurrence of the circulation patterns in the development of extreme temperature events (heat and cold waves, cold surges, frosts, and snowfalls) was also evaluated. The circulation types that induce significant anomalies of T MAX and T MIN were found to be predominant in their progress. The characterization of the relationship between circulation and surface variables together with their main properties (frequency, persistence, distribution, and temporal variability) is a basic diagnostic tool for forecasting studies on short, medium, or long terms and, therefore, for planning preventative measures against extreme events. In this sense, this paper makes a useful contribution to the characterization of this relationship in southern La Plata basin. This is a motivation to continue this line of investigation, taking into account that this study did not include the analysis of other circulation variables and other circulation-to-environment transference functions, which could be a subject for future research. Acknowledgments. This work was supported by Grants UBA and UBA of the Universidad de Buenos Aires, by the PIP of CONICET, and by the CLARIS LPB Project (European Community s Seventh Framework Programme under Grant Agreement ). REFERENCES Cerne, S. B., and M. M. Rusticucci, 1997: Estudio de la situacion sinoptica asociada con la ola de frıo extrema de febrero de 1996 (A study of the synoptic situation associated with the extreme cold wave of February 1996). Meteorologica, 22, 5 17., C. S. Vera, and B. Liebmann, 2007: The nature of a heat wave in eastern Argentina occurring during SALLJEX. Mon. Wea. Rev., 135, Escobar, G., R. H. Compagnucci, and S. A. Bishoff, 2004: Sequence patterns of 1000 hpa and 500 hpa geopotential height fields associated with cold surges over Central Argentina. Atmosfera, 17, Espinoza, J. C., J. Ronchail, M. Lengaigne, N. Quispe, Y. Silva, M. L. Bettolli, G. Avalos, and A. Llacza, 2013: Revisiting wintertime cold air intrusions at the east of the Andes: Propagating features from subtropical Argentina to Peruvian Amazon and relationship with large-scale circulation patterns. Climate Dyn., 41, Huth, R., 2010: Synoptic-climatological applicability of circulation classifications from the COST733 collection: First results. J. Phys. Chem. Earth, 35, Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, M uller, G. V., and G. J. Berri, 2007: Atmospheric circulation associated with persistent generalized frosts in Central-Southern South America. Mon. Wea. Rev., 135, ,R.H.Compagnucci,M.Nu~nez, and A. Salles, 2003: Surface circulation associated with frost in the wet Pampas. Int. J. Climatol., 23, Penalba, O. C., and M. L. Bettolli, 2011: Climate change impacts on atmospheric circulation and daily precipitation in the Argentine Pampas region. Climate Change: Geophysical Foundations and Ecological Effects, J. Blanco and H. Kheradmand, Eds., InTech, Rusticucci, M. M., and W. Vargas, 1995: Synoptic situations related to spells of extreme temperatures over Argentina. Meteor. Appl., 2, Salio, P., C. Campetella, J. Ruiz, Y. Garcia Skabar, and M. Nicolini, 2006: Nevadas en el sudeste bonaerense: Climatologıasinoptica y un caso de studio (Snowfalls in the southeastern Buenos Aires region: Synoptic climatology and case study). Meteorologica, 31, Seluchi, M., and J. Marengo, 2000: Tropical-midlatitude exchange of air masses during summer and winter in South America: Climatic aspects and examples of intense events. Int. J. Climatol., 20, Solman, S. A., and C. G. Menendez, 2003: Weather regimes in the South American sector and neighbouring oceans during winter. Climate Dyn., 21, Tencer, B., M. M. Rusticucci, P. Jones, and D. Lister, 2011: A southeastern South American daily gridded dataset of observed surface minimum and maximum temperature for Bull. Amer. Meteor. Soc., 92, Vera, C. S., and P. K. Vigliarolo, 2000: Diagnostic study of cold-air outbreaks over South America. Mon. Wea. Rev., 128, 3 24.,, and E. H. Berbery, 2002: Cold season synoptic-scale waves over subtropical South America. Mon. Wea. Rev., 130, Wilks, D. F., 1995: Statistical Methods in the Atmospheric Sciences. Academic Press, 467 pp. Yarnal, B., and J. D. Draves, 1993: A synoptic climatology of stream flow and acidity. Climate Res., 2,