J. P. Palutikof

A review of methods to calculate extreme wind speeds

Methods to calculate extreme wind speeds are described and reviewed, including ‘classical’ methods based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD), and approaches designed specifically to deal with short data sets. The emphasis is very much on the needs of users who seek an accurate method to derive extreme wind speeds but are not fully conversant with up-to-date developments in this complex subject area. First, ‘standard’ methods are reviewed: annual maxima, independent storms, r-largest extremes with the GEV distribution, and peak-over-threshold extremes with the GPD. Techniques for calculating the distribution parameters and quantiles are described. There follows a discussion of the factors which must be considered in order to fulfil the criterion that the data should be independent and identically distributed, and in order to minimize standard errors. It is commonplace in studies of extreme wind speeds that the time series available for analysis are very short. Finally, therefore, the paper deals with techniques applicable to data sets as short as two years, including simulation modelling and methods based on the parameters of the parent distribution.

Precipitation Scenarios over Iberia: A Comparison between Direct GCM Output and Different Downscaling Techniques

Abstract The Iberian rainfall regime is characterized by a strong seasonal cycle and large interannual variability. Typically, frequency distributions of monthly precipitation present a large spread of values, implying frequent episodes of very wet or very dry years. Unfortunately, the most recent generation of general circulation models (GCMs) still has serious problems when modeling monthly precipitation over southern Europe. However, these models are able to reproduce the main patterns of atmospheric circulation, such as those derived from a principal component analysis of the sea level pressure anomaly field. Many downscaling techniques have been developed in recent years, all having in common the need to establish statistical links between the large-scale circulation and the observed precipitation at a local or regional scale. The final objective is usually the application of such transfer functions to GCM output. In this work, linear and nonlinear downscaling transfer functions are developed based o...

Development of daily rainfall scenarios for southeast Spain using a circulation-type approach to downscaling

A method for downscaling from the relatively coarse General Circulation Model (GCM) spatial scale to the finer spatial scale required for impact assessment has been developed and tested in the Guadalentin Basin, southeast Spain. The method uses a circulation-type approach and relates large-scale patterns of a predictor variable, gridded sea level pressure, to local values of a surface climate variable (daily rainfall at six stations). The large-scale patterns are defined using an automated version of the Lamb Weather Type classification scheme, originally developed for the British Isles. It is demonstrated that this scheme can be successfully transferred to another region, southeast Spain. The 14 basic circulation types are combined into eight groups. These provide a legitimate basis for downscaling because each has a characteristic pressure pattern which produces the expected type and direction of flow over the study region. Furthermore, a set of consistent and distinct relationships is identified between these circulation types and daily rainfall in the Guadalentin Basin. The ability of the GCM to reproduce the observed circulation types is assessed before applying these relationships to control and perturbed-run GCM output using a statistical weather generator. The effects of the GCM’s failure to reproduce the observed frequency of the circulation types are detectable in the weather generator output. The GCM changes in SLP and circulation-type frequency between the control and perturbed-runs are generally small. Nonetheless the weather generator results indicate significant changes in the number of rain days in spring and summer. These scenarios are presented as illustrative results rather than as reliable predictions. It is concluded that the circulation-type based approach to downscaling offers great potential.

Climate and Climate Impact Scenarios for Europe in a Warmer World

Abstract Scenarios for Europe in a warmer world, such as may result from increased atmospheric carbon dioxide levels, have been constructed using the early 20th century warming as an analogue. Mean temperature, Precipitation and pressure patterns for the period 1934–53 were compared with those for 1901–20. These are the warmest and cooler twenty-year periods this century based on Northern Hemisphere annual mean surface air temperature data, differing by 0.4°C. The climate scenarios show marked subregional scale differences from season to season, and individual season scenarios often show little similarity to the annual scenario. Temperature scenarios show warming for the annual mean and for spring, summer and autumn. The largest positive changes are found in higher latitudes. Winters over a large part of Europe are actually cooler and show greater interannual variability during the warmer period. These changes appear to be associated with a greater frequency of blocking activity. Precipitation changes occ...

Tests of the Generalized Pareto Distribution for Predicting Extreme Wind Speeds

Extreme wind speed predictions are often based on statistical analysis of site measurements of annual maxima, using one of the Generalized Extreme Value (GEV) distributions. An alternative method applies one of the Generalized Pareto Distributions (GPD) to all measurements over a chosen threshold (peaks over threshold). This method increases the number of measurements included in the analysis, and correspondingly reduces the statistical uncertainty of quantile variances, but raises other important questions about, for example, event independence and the choice of threshold. Here an empirical study of the influence of event independence and threshold choice is carried out by performing a GPD analysis of gust speed maxima from five island sites in the north of Scotland. The expected invariance of the GPD shape parameter with choice of threshold is utilized to look for changes of characteristic wind speed behavior with threshold. The impact of decadal variability in wind on GEV and GPD extreme wind speed predictions is also examined, and these predictions are compared with those from the simpler Gumbel and exponential forms.

The Simulation of Daily Temperature Time Series from GCM Output. Part I: Comparison of Model Data with Observations

For climate change impact analyses, local scenarios of surface variables at the daily scales are frequently required. Empirical transfer functions are a widely used technique to generate scenarios from GCM data at these scales. For successful downscaling, the impact analyst should take into account certain considerations. First, it must be demonstrated that the GCM simulations of the required variable are unrealistic and therefore that downscaling is required. Second, it must be shown that the GCM simulations of the selected predictor variables are realistic. Where errors occur, attempts must be made to compensate for their effect on the transfer function‐ generated predictions or, where this is not possible, the effect on the transfer function‐generated climate series must be understood. Third, the changes in the predictors between the control and perturbed simulation must be examined in the light of the implications for the change in the predicted variable. Finally, the effect of decisions made during the development of the transfer functions on the final result should be explored. This study, presented in two parts, addresses these considerations with respect to the development of local scenarios for daily maximum (TMAX) and minimum (TMIN) temperature for two sites, one in North America (Eau Claire, Michigan) and one in Europe (Alcantarilla, Spain). Part I confirms for a selected GCM that simulations of daily TMAX and TMIN, whether taken from the nearest land grid point, or obtained by interpolation to the site location, are inadequate. Differences between the GCM 1 3 CO2 and observed temperature series arise because of a 08C threshold in the model data. At both sites, variability is suppressed during periods affected by the threshold. The thresholds persist into the perturbed simulation, affecting not only GCM-predicted 2 3 CO2 temperatures but also, because the duration and timing of the threshold effect changes in the perturbed simulation, the magnitude and seasonal distribution of the 2 3 CO2 ‐1 3CO2 GCM differences. Comparison of modeled and observed 500-hPa geopotential height (Z500) and sea level pressure (SLP) shows that, although systematic errors of the type associated with the 08C threshold in the temperature data are absent, significant errors do occur in certain seasons at both sites. For example, SLP is poorly modeled at Alcantarilla, where the control and observed means differ significantly in every season. The worst results at both sites are in summer. These results will affect the performance of the transfer functions when initialized with model data. Whereas little change is found to occur in SLP at either site between the 1 3 CO2 and 2 3 CO2 simulation, there is a noticeable increase in Z500. Other things being equal, therefore, the temperature changes predicted by the transfer functions are likely to be greatest when Z500 contributes the most to the explained variances. In Part II, a range of transfer functions are developed from the free atmosphere variables and validated, using observations. The performance of these transfer functions when initialized with model data is evaluated in the light of the findings in Part I. The sensitivity of the perturbed climate scenarios to a range of user decisions is explored.

The Simulation of Daily Temperature Time Series from GCM Output. Part II: Sensitivity Analysis of an Empirical Transfer Function Methodology

Abstract Empirical transfer functions have been proposed as a means for “downscaling” simulations from general circulation models (GCMs) to the local scale. However, subjective decisions made during the development of these functions may influence the ensuing climate scenarios. This research evaluated the sensitivity of a selected empirical transfer function methodology to 1) the definition of the seasons for which separate specification equations are derived, 2) adjustments for known departures of the GCM simulations of the predictor variables from observations, 3) the length of the calibration period, 4) the choice of function form, and 5) the choice of predictor variables. A modified version of the Climatological Projection by Model Statistics method was employed to generate control (1 × CO2) and perturbed (2 × CO2) scenarios of daily maximum and minimum temperature for two locations with diverse climates (Alcantarilla, Spain, and Eau Claire, Michigan). The GCM simulations used in the scenario developm...

Generating Rainfall and Temperature Scenarios at Multiple Sites: Examples from the Mediterranean

A statistical downscaling methodology was implemented to generate daily time series of temperature and rainfall for point locations within a catchment, based on the output from general circulation models. The rainfall scenarios were constructed by a two-stage process. First, for a single station, a conditional first-order Markov chain was used to generate wet and dry day successions. Then, the multisite scenarios were constructed by sampling from a benchmark file containing a daily time series of multiple-site observations, classified by season, circulation weather type, and whether the day is wet or dry at the reference station. The temperature scenarios were constructed using deterministic transfer functions initialized by free atmosphere variables. The relationship between the temperature and rainfall scenarios is established in two ways. First, sea level pressure fields define the circulation weather types underpinning the rainfall scenarios and are used to construct predictor variables in the temperature scenarios. Second, separate temperature transfer functions are developed for wet and dry days. The methods were evaluated in two Mediterranean catchments. The rainfall scenarios were always too dry, despite the application of Monte Carlo techniques in an attempt to overcome the problem. The temperature scenarios were generally too cool. The scenarios were used to explore the occurrence of extreme events, and the changes predicted in response to climate change, taking the example of temperature. The nonlinear relationship between changes in the mean and changes at the extremes was clearly demonstrated.

THE IMPACT OF THE ANOMALOUS WEATHER OF 1995 ON THE U.K. ECONOMY

This study assesses selected impacts on tertiary activities of the anomalously hot summer of 1995 and warm period from November 1994 through October 1995 in the U.K. Over this period, the mean Central England temperature was 1.6 °C above the 1961–1990 normal, representing the highest mean 12-month temperature since the start of the Central England temperature record in 1659. The study is distinguished by its breadth of coverage, for it includes tertiary sectors and activities. Although impacts in tertiary activities are often not included in assessments of the potential impacts of climatic change, many of these activities are very important to the U.K. economy, and therefore even a small perturbation in output due to a weather extreme can have significant implications for the economy as a whole. The activities and sectors studied include energy consumption, retailing and manufacturing, construction and buildings, tourism, health, human behaviour, and fires. Both negative and positive impacts were incurred within most sectors. Net positive impacts (to the general public) were found convincingly for energy consumption and health, and clear negative impacts for buildings insurance and fires. Sectors which show clear differences in their response to winter and summer warm anomalies are energy consumption, tourism and health (greater sensitivity to winter anomalies) and buildings insurance and fires (greater sensitivity to summer anomalies). Changes in sensitivity to climate extremes may have occurred over time, and a comparison of impacts of the 1995 anomalous weather with the unusually warm dry period of 1975–1976 is approached for several series.

Estimation of sector roughness lengths and the effect on prediction of the vertical wind speed profile

An estimate of roughness length is required by some atmospheric models and is also used in the logarithmic profile to determine the increase of wind speed with height under neutral conditions. The choice of technique for determining roughness lengths is generally constrained by the available input data. Here, we compare sets of roughness lengths derived by different methods for the same site and evaluate their impact on the prediction of the vertical wind speed profile.Wind speed and direction data have been collected at four heights over a three-year period at the North Norfolk Wind Monitoring Site. Wind speed profiles were used to generate sector roughness lengths based on the logarithmic profile formula. This is the only direct way of determining roughness lengths. The simplest and cheapest method is to use maps with published tables giving roughness length estimates for different terrain types. Alternatively Wieringa (1976, 1986) and Beljaars (1987) give formulae for determining roughness lengths from wind speed gusts or standard deviations.The four sets of estimated roughness lengths vary considerably. They were used to estimate 34 m wind speeds from 12.7 m observations. The profile-derived roughnesses are used simply as a check on the prediction of the wind speed profiles. The terrain-derived roughness lengths give reasonable results. Gust-derived and standard deviation roughnesses both predict wind speeds which are lower than the observed ones. The error is greater in the case of standard deviation roughnesses. If stability corrections are applied in the prediction of the vertical wind speed profile, the results are considerably improved.