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Matilde Rusticucci and Bárbara Tencer

Abstract

Extreme temperature events are one of the most studied extreme events since their occurrence has a huge impact on society. In this study, the frequency of occurrence of absolute extreme temperature events in Argentina is analyzed. Four annual extremes are defined based on minimum and maximum daily data: the highest maximum (minimum) temperature of the year, and the lowest maximum (minimum) temperature of the year. Applying the extreme value theory (EVT), a generalized extreme value (GEV) distribution is fitted to these extreme indices and return values are calculated for the period 1956–2003. Its spatial distribution indicates that, for warm extremes, maximum temperature (Tx) is expected to be greater than 32°C at least once every 100 yr throughout the country (reaching values even higher than 46°C in the central region), while minimum temperature (Tn) is expected to exceed 16°C (reaching 30°C in the central and northern regions). Cold annual extremes show larger gradients across the country, with Tx being lower than 8°C at least once every 100 yr, and Tn lower than 0°C every 2 yr, with values even less than −10°C in the southwestern part of the country.

However, the frequency of occurrence of climatic extremes has changed throughout the globe during the twentieth century. Changes in return values of annual temperature extremes due to the 1976–77 climatic shift at six long-term datasets are then analyzed. The lowest Tx of the year is the variable in which the 1976–77 shift is less noticeable. At all the stations studied there is a decrease in the probability of occurrence of the highest Tx if the study is based on more recent records, while the frequency of occurrence of the highest Tn increases at some stations and decreases at others. This implies that in the “present climate” (after 1977) there is a greater frequency of occurrence of high values of Tn at Observatorio Central Buenos Aires and Río Gallegos together with a lower frequency of occurrence of high values of Tx, leading to a decrease in the annual temperature range.

The most noticeable change in return values due to the 1976–77 shift is seen in Patagonia where the 10-yr return value for the highest Tn increases from 13.7°C before 1976 to 18.6°C after 1977. That is, values of the highest Tn that occurred at least once every 10 yr in the “past climate” (before 1976) now happened more than once every 2 yr.

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Matilde Rusticucci and Mariana Barrucand

Abstract

In this note, changes in temperature extremes over a 40-yr period are analyzed, based on daily minimum and maximum temperatures over Argentina. Trend analysis was performed on seasonal means, standard deviations, and extremes (5th and 95th percentiles) over the 1959–98 period. The strongest (positive) changes over time occurred in mean summer minimum temperature, whereas the standard deviation decreased. Mean maximum temperatures mostly decrease over time in summer over northern Argentina, but they increase in Patagonia (southern Argentina). Generally, negative trends were obtained in the number of cold nights and warm days per summer, while the number of warm nights and cold days has increased at certain locations. Patagonia shows many stations with an increasing number of warm days and nights in winter and a decreasing number of cold days and nights in summer. The summer mean temperature is more sensitive to extremes than the winter one. In summer, the increase in mean temperature is more strongly related to the increase in the number of warm days and nights than to a decrease in the number of cold days and nights. In winter, the region with the highest correlation was found in Patagonia, while in the most productive area (La Pampa, Argentina), very little or nonsignificant association exists between mean temperature and the occurrence of warm or cold days.

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Natalia Zazulie, Matilde Rusticucci, and Susan Solomon

Abstract

The climate observations at Orcadas represent the only southern high-latitude site where data span more than a century, and its daily measurements are presented for the first time in this paper. Although limited to a single station, the observed warming trends are among the largest found anywhere on the earth, facilitating the study of changes in extreme temperatures as well as averages. Factors that may influence Antarctic climate include natural variability; changes in greenhouse gases; and, since about the mid-1970s, the development of the ozone hole. The seasonality of observed warming and its temporal evolution during the century are both key for interpretations of Antarctic climate change. No statistically significant climate trends are observed at Orcadas from 1903 to 1950. However, statistically significant warming is evident at Orcadas throughout all four seasons of the year since 1950. Particularly in austral fall and winter, the warming of the cold extremes (coldest 5% and 10% of days) substantially exceeds the warming of the mean or of the warmest days, providing a key indicator for cold season Antarctic climate change studies. Trends in the summer season means and extremes since 1970 are approximately twice as large as those observed earlier, supporting suggestions of additional regional warming in that season because of the effects of ozone depletion on the circulation. Further, in the spring and summer seasons, significant mean warming also occurred prior to the development of the Antarctic ozone hole (i.e., 1950–70), supporting an important role for processes other than ozone depletion, such as greenhouse gas increases, for the climate changes.

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Matilde M. Rusticucci and Vernon E. Kousky

Abstract

This paper compares surface-station temperature observations over Argentina with gridpoint analyses available in the NCEP–NCAR reanalysis dataset. The primary objective is to determine whether the maximum and minimum surface temperatures from the reanalysis can be used to compute statistics on the occurrence of extreme events. The extreme range of topography and geography of Argentina is viewed as a severe test for the reanalysis data. Good agreement, on both the daily and monthly timescales, between the station data and the reanalysis gridpoint data is found over the low-elevation regions in central and eastern Argentina. The agreement is relatively poor for summertime maximum temperatures over northern Argentina. The reanalysis data underestimate the intensity of extreme warm events over northern and southern Argentina and overestimate extreme cold events during winter over central Argentina. High-elevation areas in western Argentina have the poorest correspondence throughout the year. Thus, the NCEP–NCAR reanalysis data have to be used with caution for studies of the magnitude of day-to-day temperature changes. The results of this study indicate that the NCEP–NCAR reanalysis data are sufficient for determining the timing of midlatitude events but are not sufficient for determining the amplitude and frequency in the subtropics and in regions of high relief. The use of anomalies tends to improve the amount of agreement between the reanalysis data and station observations.

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Bárbara Tencer, Matilde Rusticucci, Phil Jones, and David Lister

This study presents a southeastern South American gridded dataset of daily minimum and maximum surface temperatures for 1961–2000. The data used for the gridding are observed daily data from meteorological stations in Argentina, Brazil, Paraguay, and Uruguay from the database of the European Community's Sixth Framework Programme A Europe–South America Network for Climate Change Assessment and Impact Studies in La Plata Basin (EU FP6 CLARIS LPB), with some additional data series. This gridded dataset is new for the region, not only for its spatial and temporal extension, but also for its temporal resolution. The region for which the gridded dataset has been developed is 20°–40°S, 45°–70°W, with a resolution of 0.5° latitude × 0.5° longitude. Since the methodology used produces an estimation of gridbox averages, the developed dataset is very useful for the validation of regional climate models. The comparison of gridded and observed data provides an evaluation of the usefulness of the interpolated data. According to monthly-mean values and daily variability, the methodology of interpolation developed during the EU FP6 ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) project for its application in Europe is also suitable for southeastern South America. Root-mean-square errors for the whole region are 1.77°C for minimum temperature and 1.13°C for maximum temperature. These errors are comparable to values obtained for Europe with the same methodology.

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