[1] 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 nearcomplete 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.
[1] We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period . 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.
We describe the construction of a 10' latitude/longitude data set of mean monthly surface climate over global land areas, excluding Antarctica. The climatology includes 8 climate elements -precipitation, wet-day frequency, temperature, diurnal temperature range, relative humidity, sunshine duration, ground frost frequency and windspeed -and was interpolated from a data set of station means for the period centred on 1961 to 1990. Precipitation was first defined in terms of the parameters of the Gamma distribution, enabling the calculation of monthly precipitation at any given return period. The data are compared to an earlier data set at 0.5º latitude/longitude resolution and show added value over most regions. The data will have many applications in applied climatology, biogeochemical modelling,
The authors describe the construction of a 0.5° latitude/longitude gridded dataset of monthly terrestrial surface climate over for the period 1901-1996. The dataset comprises a suite of 7 climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover and ground-frost frequency. The spatial coverage extends over all land areas, excluding Antarctica. Fields of monthly climate anomalies, relative the 1961-1990 mean, were interpolated from surface climate data. The anomaly grids were then added to a 1961-1990 mean monthly climatology (described in Part I) to arrive at grids of monthly climate. The primary variables, precipitation, mean temperature and diurnal temperature range, were interpolated directly from station observations. The resulting time-series are compared with other, coarser resolution, datasets of similar temporal extent. The remaining climatic elements, termed secondary variables, were interpolated from merged datasets, comprising station observations and, in regions where there were no station data, synthetic data estimated using predictive relationships with the primary variables, which are described and evaluated. It is argued that this new dataset represents an advance other products because (i) it has higher spatial resolution than other datasets of similar temporal extent, (ii) it has longer temporal coverage than other products of similar spatial resolution; (iii) it encompasses a more extensive suite of surface climate variables than available elsewhere and (iv) the construction method ensures that strict temporal fidelity is maintained. The dataset is available from the Climatic Research Unit.
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