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Francis W. Zwiers

Abstract

The climate literature contains a considerable amount of indirect evidence that there is a connection betweenthe size of the spring Tibetan snowpack and the strength of the subsequent Asian summer monsoon. This paperreports on a study that was conducted to search for evidence of a direct snow-monsoon interaction in a simulatedclimatology derived from two long integrations of the Canadian Climate Centre's GCM version 1. Statisticalmethods based on a combination of empirical orthogonal function analysis and canonical correlation analysiswere the primary investigative tools. Only a weak signal was found. It is therefore concluded that either thesimulated variability ofthe snow on Tibet is too small, the model does not react appropriately to the simulatedvariability, or the true natural snow-monsoon mechanism is weak and any snow-monsoon connection reliesupon a third factor. The first possibility is considered to be remote: the model simulates substantial interannualvariability of Tibetan snow. The second and third possibilities are more likely. In particular, the physical mechanism that is thought to connect Tibetan snow with the Asian monsoon may not be properly simulated inthe model.

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Francis W. Zwiers

Abstract

Resampling procedures include hypothesis testing methods based on Permutation Procedures and interval estimation methods based on bootstrap procedures. The former are widely used in the analysis of climate experiments conducted with general circulation models (GCMs) and in the comparison of the simulated and observed climates. The latter are used less frequently than their flexibility and utility warrants. Both resampling techniques are powerful tools, which provide elegant means of overcoming fundamental statistical difficulties encountered in the analysis of observed and simulated climate data. Unfortunately, inference based on both resampling schemes are as sensitive to the effects of serial correlation as classical statistical methods. These tools must therefore be used with the same amount of caution as other statistical methods when it is suspected that the data might be serially correlated.

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Francis Zwiers and Hans Von Storch

Abstract

The class of “regime dependent autoregressive” time series models (RAMs) is introduced. These nonlinear models describe variations of the moments of nonstationary time series by allowing parameter values to change with the state of an ancillary controlling time series and possibly an index series. The index series is used to indicate deterministic seasonal and regimal changes with time. Fitting and diagnostic procedures are described in the paper.

RAMs are fitted to a 102-year seasonal mean tropical Pacific sea surface temperature index time series. The models are controlled by a seasonal index series and one of two ancillary time series: seasonal mean Adelaide sea level pressure and Indian monsoon rainfall, which have previously been identified as possible precursors of the extremes of the Southern Oscillation (SO).

Analysis of the fitted models gives clear evidence for the seasonal variation of the statistical characteristics of the SO. There is strong evidence that the annual cycle of the SO index depends upon the state of the SO as represented by the ancillary time series. There is weaker evidence which suggests that its autocorrelation structure is also state dependent.

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Francis W. Zwiers and Xuebin Zhang

Abstract

Using an optimal detection technique, the extent to which the combined effect of changes in greenhouse gases and sulfate aerosols (GS) may be detected in observed surface temperatures is assessed in six spatial domains decreasing in size from the globe to Eurasia and North America, separately. The GS signal is detected in the annual mean near-surface temperatures of the past 50 yr in all domains. It is also detected in some seasonal mean temperatures of the past 50 yr, with detection in more seasons in larger domains.

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Habs von Storch and Francis W. Zwiers

Abstract

A difficulty with the statistical techniques which are ordinarily used in the analysis of climate sensitivity experiments is that they do not identify the stable, or recurrent, aspects of the experimental response. Therefore, a new concept called “recurrence” is proposed. With this concept it is possible to identify the parts of the response which are likely to recur with an a priori likelihood each time a new experimental realization is obtained. A variety of statistical tests which may be used to assess an a priori level of recurrence by means of limited samples is suggested.

A recurrence analysis is performed with data simulated by the Canadian Climate Centre general circulation model forced with climatological sea surface temperatures (SSTs) and with several El Ninño SST anomalies. All considered SST anomalies, a positive and a negative doubled standard Rasmusson and Carpenter anomaly and the winter 1982/83 anomaly excite a globally significantly response in terms of height and temperature. However, only part of the significant response is also recurrent. In the cold SST anomaly experiment, recurrence is confined to a minor part of the tropics. In the warm SST anomaly runs, recurrence is found in most of the tropics and partly over the northeastern Pacific. These results indicate that equatorial Pacific SST anomalies are associated with a rather limited predictive value, even if the anomalies are very strong.

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Francis W. Zwiers and Viatcheslav V. Kharin

Abstract

Changes due to CO2 doubling in the extremes of the surface climate as simulated by the second-generation circulation model of the Canadian Centre for Climate Modelling and Analysis are studied in two 20-yr equilibrium simulations. Extreme values of screen temperature, precipitation, and near-surface wind in the control climate are compared to those estimated from 17 yr of the NCEP–NCAR reanalysis data and from some Canadian station data.

The extremes of screen temperature are reasonably well reproduced in the control climate. Their changes under CO2 doubling can be connected with other physical changes such as surface albedo changes due to the reduction of snow and sea ice cover as well as a decrease of soil moisture in the warmer world.

The signal in the extremes of daily precipitation and near-surface wind speed due to CO2 doubling is less obvious. The precipitation extremes increase almost everywhere over the globe. The strongest change, over northwest India, is related to the intensification of the summer monsoon in this region in the warmer world. The modest reduction of wind extremes in the Tropics and middle latitudes is consistent with the reduction of the meridional temperature gradient in the 2×CO2 climate. The larger wind extremes occur in the areas where sea ice has retreated.

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Francis W. Zwiers and Hans von Storch

Abstract

The comparison of means derived from samples of noisy data is a standard pan of climatology. When the data are not serially correlated the appropriate statistical tool for this task is usually the conventional Student's t-test. However, frequently data are serially correlated in climatological applications with the result that the t test in its standard form is not applicable. The usual solution to this problem is to scale the t statistic by a factor that depends upon the equivalent sample size ne.

It is shown, by means of simulations, that the revised t tea is often conservative (the actual significance level is smaller than the specified significance level) when the equivalent sample size is known. However, in most practical cases the equivalent sample size is not known. Then the test becomes liberal (the actual significance level is greater than the specified significance level). This systematic error becomes small when the true equivalent sample size is large (greater than approximately 30).

The difficulties inherent in difference of means tests when there is serial dependence are reexamined. Guidelines for the application of the “usual” t test are provided and two alternative tests are proposed that substantially improve upon the “usual” t test when samples are small.

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Bárbara Tencer, Andrew Weaver, and Francis Zwiers

Abstract

The occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

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Viatcheslav V. Kharin and Francis W. Zwiers

Abstract

The relative operating characteristic (ROC) is a measure of the quality of probability forecasts that relates the hit rate to the corresponding false-alarm rate. This paper examines some aspects of the ROC curve for probability forecasts of three equiprobable categories (below normal, near normal, and above normal) in the framework of a simple analog of a climate forecasting system. The insensitivity of the ROC score to some types of forecast biases is discussed and the link to deterministic potential predictability is established in the context of the simple forecasting system. The findings are illustrated with a collection of 24-member ensemble hindcasts of seasonal mean 700-hPa temperature produced with the second-generation general circulation model of the Canadian Centre for Climate Modelling and Analysis.

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Viatcheslav V. Kharin and Francis W. Zwiers

Abstract

The extremes of surface temperature, precipitation, and wind speed and their changes under projected changes in radiative forcing are examined in an ensemble of three transient climate change simulations for the years 1900–2100 conducted with the global coupled model of the Canadian Centre for Climate Modelling and Analysis. The evolution of the greenhouse gases and aerosols in these simulations is consistent with the Intergovernmental Panel on Climate Change 1992 scenario A. The extremes are analyzed in three 21-yr time periods centered at years 1985, 2050, and 2090.

The model simulates reasonably well the extremes of the contemporary near-surface climate. Changes in extremes of daily maximum and daily minimum temperature are distinctively different and are related to changes in the mean screen temperature, soil moisture, and snow and sea-ice cover. Extreme precipitation increases almost everywhere on the globe. Relative change in extreme precipitation is larger than change in total precipitation. Extreme wind speed in the extratropics changes only modestly. Changes in duration of extended wet and dry periods are consistent with changes in total precipitation. There are temperature-related changes in cooling and heating degree days.

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