[1] In this study, we present the collation and analysis of the gridded land-based dataset of indices of temperature and precipitation extremes: HadEX2. Indices were calculated based on station data using a consistent approach recommended by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices, resulting in the production of 17 temperature and 12 precipitation indices derived from daily maximum and minimum temperature and precipitation observations. High-quality in situ observations from over 7000 temperature and 11,000 precipitation meteorological stations across the globe were obtained to calculate the indices over the period of record available for each station. Monthly and annual indices were then interpolated onto a 3.75 Â 2.5 longitude-latitude grid over the period 1901-2010. Linear trends in the gridded fields were computed and tested for statistical significance. Overall there was very good agreement with the previous HadEX dataset during the overlapping data period. Results showed widespread significant changes in temperature extremes consistent with warming, especially for those indices derived from daily minimum temperature over the whole 110 years of record but with stronger trends in more recent decades. Seasonal results showed significant warming in all seasons but more so in the colder months. Precipitation indices also showed widespread and significant trends, but the changes were much more spatially heterogeneous compared with temperature changes. However, results indicated more areas with significant increasing trends in extreme precipitation amounts, intensity, and frequency than areas with decreasing trends.Citation: Donat, M. G., et al. (2013), Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset,

Water vapour is the most important contributor to the natural greenhouse effect, and the amount of water vapour in the atmosphere is expected to increase under conditions of greenhouse-gas-induced warming, leading to a significant feedback on anthropogenic climate change. Theoretical and modelling studies predict that relative humidity will remain approximately constant at the global scale as the climate warms, leading to an increase in specific humidity. Although significant increases in surface specific humidity have been identified in several regions, and on the global scale in non-homogenized data, it has not been shown whether these changes are due to natural or human influences on climate. Here we use a new quality-controlled and homogenized gridded observational data set of surface humidity, with output from a coupled climate model, to identify and explore the causes of changes in surface specific humidity over the late twentieth century. We identify a significant global-scale increase in surface specific humidity that is attributable mainly to human influence. Specific humidity is found to have increased in response to rising temperatures, with relative humidity remaining approximately constant. These changes may have important implications, because atmospheric humidity is a key variable in determining the geographical distribution and maximum intensity of precipitation, the potential maximum intensity of tropical cyclones, and human heat stress, and has important effects on the biosphere and surface hydrology.

Thermal comfort is quantified in 15 regions using the wet-bulb globe temperature (WBGT), examining past and future rates of thresholds exceedance corresponding to moderate, high, and extreme heat (28, 32, and 35°C, respectively). As recent changes to thermal comfort appear to be dominated by temperature and humidity, a WBGT approximation based only on these is used. A new homogenised dataset from 1973 to 2003 is developed which provides WBGT daily means, daily maximums averaged over 5-day periods, and the highest extreme for each 5-day period; recent trends are positive for all regions except northeast USA and northeast Australia. A simple model for predicting summertime threshold exceedance rates, with a fixed distribution of anomalies about the seasonal mean, is found to adequately predict changes for the above quantities given seasonal mean values. This model is used to predict the impact of regional 1-5°C temperature increases on WBGT exceedance rates with no change in relative humidity. Results show that heat events may worsen as much, or more, in humid tropical and mid-latitude regions even if they warm less than the global average, due to greater absolute humidity increases. A further 2°C warming from the present is sufficient to push peak WBGT above 35°C, an extreme heat event, in all regions except the UK.An ensemble of HadCM3 climate model simulations is used to investigate likely regional changes in mean summertime temperature, relative humidity and WBGT under an A1B scenario for the 2020s and 2050s. Unsurprisingly, simulated regional changes often depart significantly from the global average, and the impact of regional changes in relative humidity is not always negligible. Increases in WBGT are nonetheless expected in all regions, and are more predictable than increases in temperature at least in mid-latitude regions owing to the compensating effects of humidity. 