A. M. G. Klein Tank

Global observed changes in daily climate extremes of temperature and precipitation

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950-2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three-step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three-dimensional thin-plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years. Copyright 2008 by the American Geophysical Union.

A regional peaks-over-threshold model in a nonstationary climate

Regional frequency analysis is often used to reduce the uncertainty in the estimation of distribution parameters and quantiles. In this paper a regional peaks-over-threshold model is introduced that can be used to analyze precipitation extremes in a changing climate. We use a temporally varying threshold, which is determined by quantile regression for each site separately. The marginal distributions of the excesses are described by generalized Pareto distributions (GPD). The parameters of these distributions may vary over time and their spatial variation is modeled by the index flood (IF) approach. We consider different models for the temporal dependence of the GPD parameters. Parameter estimation is based on the framework of composite likelihood. Composite likelihood ratio tests that account for spatial dependence are used to test the significance of temporal trends in the model parameters and to test the IF assumption. We apply the method to gridded, observed daily precipitation data from the Netherlands for the winter season. A general increase of the threshold is observed, especially along the west coast and northern parts of the country. Moreover, there is no indication that the ratio between the GPD scale parameter and the threshold has changed over time, which implies that the scale parameter increases by the same percentage as the threshold. These positive trends lead to an increase of rare extremes of on average 22% over the country during the observed period.

Regression model for generating time series of daily precipitation amounts for climate change impact studies

The precipitation amounts on wet days at De Bilt (the Netherlands) are linked to temperature and surface air pressure through advanced regression techniques. Temperature is chosen as a covariate to use the model for generating synthetic time series of daily precipitation in a CO2 induced warmer climate. The precipitation-temperature dependence can partly be ascribed to the phenomenon that warmer air can contain more moisture. Spline functions are introduced to reproduce the non-monotonous change of the mean daily precipitation amount with temperature. Because the model is non-linear and the variance of the errors depends on the expected response, an iteratively reweighted least-squares technique is needed to estimate the regression coefficients. A representative rainfall sequence for the situation of a systematic temperature rise is obtained by multiplying the precipitation amounts in the observed record with a temperature dependent factor based on a fitted regression model. For a temperature change of 3°C (reasonable guess for a doubled CO2 climate according to the present-day general circulation models) this results in an increase in the annual average amount of 9% (20% in winter and 4% in summer). An extended model with both temperature and surface air pressure is presented which makes it possible to study the additional effects of a potential systematic change in surface air pressure on precipitation.

The effects of urbanization on the rise of the European temperature since 1960

The effects of urbanization on the rise of the European daily mean temperature is quantified by comparing European-averaged temperatures based on all meteorological stations in the European Climate Assessment and Dataset with those based on three subsets of stations: from rural areas, from areas with low growth in urbanization, and from areas characterized by relatively low-temperature increase. Land cover information is obtained using the CORINE (Coordination of Information on the Environment) data set, showing that most stations (75%) have a small percentage (up to 10%) of urban area within a 10 km radius and 81% saw no more than 1% change in urbanization between 1990 and 2006. The results show that urbanization explains 0.0026°C/decade of the annual-averaged pan-European temperature trend of 0.179°C/decade. This trend has a strong seasonality, being the largest in summer. Averaged over time, the effects of urbanization on the European-averaged temperature has a strong seasonality as well.

Relationship between sunshine duration and temperature trends across Europe since the second half of the twentieth century

Global radiation is a fundamental source of energy in the climate system. A significant impact of global radiation on temperature change is expected due to the widespread dimming/brightening phenomenon observed since the second half of the twentieth century. This work describes the analysis of 312 stations with sunshine duration (SD) series, a proxy for global radiation, and temperature series in the European Climate Assessment & Dataset (ECA&D) with data over the period 1961–2010. The relationship between SD and temperature series is analyzed for four temperature variables: maximum (Tmax), minimum (Tmin), mean temperature (Tmean), and diurnal temperature range (DTR). The analyses are performed on annual and seasonal basis. The results show strong positive correlations between SD and temperatures over Europe, with highest correlation for DTR and Tmax during the summer period. These results confirm the strong relationship between SD and temperature trends over Europe since the second half of the twentieth century. This study supports previous suggestions that dimming (brightening) has partially decreased (increased) temperatures thereby modulating the greenhouse gas induced warming rates over Europe.

Preparing local climate change scenarios for the Netherlands using resampling of climate model output

A method to prepare a set of four climate scenarios for the Netherlands is presented. These scenarios for climate change in 2050 and 2085 (compared to present-day) are intended for general use in climate change adaptation in the Netherlands. An ensemble of eight simulations with the global model EC-Earth and the regional climate model RACMO2 (run at 12 km resolution) is used. For each scenario time horizon, two target values of the global mean temperature rise are chosen based on the spread in the CMIP5 simulations. Next, the corresponding time periods in the EC-Earth/RACMO2 simulations are selected in which these target values of the global temperature rise are reached. The model output for these periods is then resampled using blocks of 5 yr periods. The rationale of resampling is that natural variations in the EC-Earth/RACMO2 ensemble are used to represent (part of the) uncertainty in the CMIP5 projections. Samples are then chosen with the aim of reconstructing the spread in seasonal temperature and precipitation changes in CMIP5 for the Netherlands. These selected samples form the basis of the scenarios. The resulting four scenarios represent 50–80% of the CMIP5 spread for summer and winter changes in seasonal means as well as a limited number of monthly statistics (warm, cold, wet and dry months). The strong point of the method—also in relation to the previous set of the climate scenarios for the Netherlands issued in 2006—is that it preserves nearly all physical inter-variable consistencies as they exist in the original model output in both space and time.

Simple Temperature Scenario for a Gulf Stream Induced Climate Change

Consequences of a Gulf Stream induced ocean surface cooling for the temperature climate of Western Europe were studied by means of a conditional perturbation of the observed daily temperature time series of the Netherlands. On days with advection of airmasses of maritime origin, the observed temperatures in the series were lowered with a fixed value, representing the influence of a cooler Atlantic Ocean. On the other days, the observed temperatures were left unchanged. The perturbation results in a decrease in the mean temperature that is almost constant over the year, and in a change in the standard deviation of the daily temperatures that is seasonally dependent. Due to preferential cooling of warm winter days, the standard deviation decreases in the winter, whereas in the other seasons the standard deviation increases as a result of preferential cooling of days with low temperatures. Although this ocean cooling scenario indicates an increase of the relative frequency of cold winters and cool summers, it is neither characterized by the occurrence of winters with unprecedented low temperatures nor by the disappearance of summer heatwaves.

Climate change scenarios for impact studies in the Netherlands

Abstract Observed relations between meteorological elements in the present-day climate are used to transform an observed daily time series into representative daily time series of a possible future climate. For point precipitation the method needs reasonable guesses of the large-scale changes in the seasonal means of surface air temperature (or the combination of surface air temperature and surface air pressure). The transformation method is described and an example is given for De Bilt (the Netherlands).

Vulnerability Assessments in the Netherlands Using Climate Scenarios

The low lying delta country The Netherlands has a long history of coping with fluctuating and changing natural and socioeconomic conditions in the river delta. Projected changes in relevant climatic conditions are being explored using a range of scenario approaches, both concerning climate and socio economic developments. This manuscript describes the convolution of this scenario approach with the necessary assessments of the various vulnerabilities in the area, guided by a number of examples where these approaches are tightly coupled.