Observed coherent changes in climatic extremes during the second half of the twentieth century
A new global dataset of derived indicators has been compiled to clarify whether fre- quency and/or severity of climatic extremes changed during the second half of the 20th century. This period provides the best spatial coverage of homogenous daily series, which can be used for calcu- lating the proportion of global land area exhibiting a significant change in extreme or severe weather. The authors chose 10 indicators of extreme climatic events, defined from a larger selection, that could be applied to a large variety of climates. It was assumed that data producers were more inclined to release derived data in the form of annual indicator time series than releasing their origi- nal daily observations. The indicators are based on daily maximum and minimum temperature series, as well as daily totals of precipitation, and represent changes in all seasons of the year. Only time series which had 40 yr or more of almost complete records were used. A total of about 3000 indicator time series were extracted from national climate archives and collated into the unique dataset described here. Global maps showing significant changes from one multi-decadal period to another during the interval from 1946 to 1999 were produced. Coherent spatial patterns of statistically signif- icant changes emerge, particularly an increase in warm summer nights, a decrease in the number of frost days and a decrease in intra-annual extreme temperature range. All but one of the temperature- based indicators show a significant change. Indicators based on daily precipitation data show more mixed patterns of change but significant increases have been seen in the extreme amount derived from wet spells and number of heavy rainfall events. We can conclude that a significant proportion of the global land area was increasingly affected by a significant change in climatic extremes during the second half of the 20th century. These clear signs of change are very robust; however, large areas are still not represented, especially Africa and South America.
Hemispheric and Large-Scale Surface Air Temperature Variations: An Extensive Revision and an Update to 2001.
This study is an extensive revision of the Climatic Research Unit (CRU) land station temperature database that is used to produce a gridbox dataset of 58 latitude 3 58 longitude temperature anomalies. The new database comprises 5159 station records, of which 4167 have enough data for the 1961‐90 period to calculate or estimate the necessary averages. Apart from the increase in station numbers compared to the earlier study in 1994, many station records have had their data replaced by newly homogenized series that have been produced by several recent studies. New versions of all the gridded datasets currently available on the CRU Web site (http:// www.cru.uea.ac.uk) have been developed. This includes combinations with marine (sea surface temperature anomalies) data over the oceans and versions with adjustment of the variance of individual gridbox series to remove the effects of changing station numbers through time. Hemispheric and global temperature averages for land areas developed with the new dataset differ slightly from those developed in 1994. Possible reasons for the differences between the new and the earlier analysis and those from the National Climatic Data Center and the Goddard Institute for Space Studies are discussed. Differences are greatest over the Southern Hemisphere and at the beginnings and ends of each time series and relate to gridbox sizes and data availability. The rate of annual warming for global land areas over the 1901‐ 2000 period is estimated by least squares to be 0.078C decade21 (significant at better than the 99.9% level). Warming is not continuous but occurs principally over two periods (about 1920‐45 and since 1975). Annual temperature series for the seven continents and the Arctic all show significant warming over the twentieth century, with significant (95%) warming for 1920‐44 for North America, the Arctic, Africa, and South America, and all continents except Australia and the Antarctic since 1977. Cooling is significant during the intervening period (1945‐76) for North America, the Arctic, and Africa.
Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs
In this paper we set out some methods that utilize the longitudinal structure of earnings of trainees and a comparison group to estimate the effectiveness of training for the 1976 cohort of CETA trainees. By fitting a components-of-variance model of earnings to the control group, and posing a simple model of program participation, we are able to predict the entire earnings histories of the trainees. The fit of these predictions to the pre-training earnings of the CETA participants provides a test of the model of earnings generation and program participation and simple check on the corresponding estimate of the effectiveness of training.Two factors appear to have a critical influence on the size of the estimated training effects: the time of the decision to participate in training and the presence or absence of individual-specific trends in earnings. We find considerable evidence that trainee earnings contain permanent, transitory,and trend-like components of selection bias. We are less successful in distinguishing empirically between alternative assumptions on the timing of the participation decision. If earnings in the year prior to training are the appropriate selection criterion, however, our estimate of the training effect for adult male CETA participants is about 300 dollars per year. Our estimates for female CETA participants are larger, and less sensitive to alternative models of program participation.
Extreme Value Analysis of Environmental Time Series: An Application to Trend Detection in Ground-Level Ozone
Several methods of analyzing extreme values are now known, most based on the extreme value limit distributions or related families. This paper reviews these techniques and proposes some extensions based on the point-process view of high-level exceedances. These ideas are illustrated with a detailed analysis of ozone data collected in Houston, Texas. There is particular interest in whether they is any trend in the data. The analysis reveals no trend in the overall levels of the series, but a marked downward trend in the extreme values.
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