The global historical climate database HCLIM.

There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.

Comparison of UTCI to selected thermal indices.

Over the past century more than 100 indices have been developed and used to assess bioclimatic conditions for human beings. The majority of these indices are used sporadically or for specific purposes. Some are based on generalized results of measurements (wind chill, cooling power, wet bulb temperature) and some on the empirically observed reactions of the human body to thermal stress (physiological strain, effective temperature). Those indices that are based on human heat balance considerations are referred to as "rational indices". Several simple human heat balance models are known and are used in research and practice. This paper presents a comparative analysis of the newly developed Universal Thermal Climate Index (UTCI), and some of the more prevalent thermal indices. The analysis is based on three groups of data: global data-set, synoptic datasets from Europe, and local scale data from special measurement campaigns of COST Action 730. We found the present indices to express bioclimatic conditions reasonably only under specific meteorological situations, while the UTCI represents specific climates, weather, and locations much better. Furthermore, similar to the human body, the UTCI is very sensitive to changes in ambient stimuli: temperature, solar radiation, wind and humidity. UTCI depicts temporal variability of thermal conditions better than other indices. The UTCI scale is able to express even slight differences in the intensity of meteorological stimuli.

Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).

The Universal Thermal Climate Index (UTCI) aimed for a one-dimensional quantity adequately reflecting the human physiological reaction to the multi-dimensionally defined actual outdoor thermal environment. The human reaction was simulated by the UTCI-Fiala multi-node model of human thermoregulation, which was integrated with an adaptive clothing model. Following the concept of an equivalent temperature, UTCI for a given combination of wind speed, radiation, humidity and air temperature was defined as the air temperature of the reference environment, which according to the model produces an equivalent dynamic physiological response. Operationalising this concept involved (1) the definition of a reference environment with 50% relative humidity (but vapour pressure capped at 20 hPa), with calm air and radiant temperature equalling air temperature and (2) the development of a one-dimensional representation of the multivariate model output at different exposure times. The latter was achieved by principal component analyses showing that the linear combination of 7 parameters of thermophysiological strain (core, mean and facial skin temperatures, sweat production, skin wettedness, skin blood flow, shivering) after 30 and 120 min exposure time accounted for two-thirds of the total variation in the multi-dimensional dynamic physiological response. The operational procedure was completed by a scale categorising UTCI equivalent temperature values in terms of thermal stress, and by providing simplified routines for fast but sufficiently accurate calculation, which included look-up tables of pre-calculated UTCI values for a grid of all relevant combinations of climate parameters and polynomial regression equations predicting UTCI over the same grid. The analyses of the sensitivity of UTCI to humidity, radiation and wind speed showed plausible reactions in the heat as well as in the cold, and indicate that UTCI may in this regard be universally useable in the major areas of research and application in human biometeorology.

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from measured and observed meteorological data.

In the present study, we investigate the determination accuracy of the Universal Thermal Climate Index (UTCI). We study especially the UTCI uncertainties due to uncertainties in radiation fluxes, whose impacts on UTCI are evaluated via the mean radiant temperature (Tmrt). We assume "normal conditions", which means that usual meteorological information and data are available but no special additional measurements. First, the uncertainty arising only from the measurement uncertainties of the meteorological data is determined. Here, simulations show that uncertainties between 0.4 and 2 K due to the uncertainty of just one of the meteorological input parameters may be expected. We then analyse the determination accuracy when not all radiation data are available and modelling of the missing data is required. Since radiative transfer models require a lot of information that is usually not available, we concentrate only on the determination accuracy achievable with empirical models. The simulations show that uncertainties in the calculation of the diffuse irradiance may lead to Tmrt uncertainties of up to ±2.9 K. If long-wave radiation is missing, we may expect an uncertainty of ±2 K. If modelling of diffuse radiation and of longwave radiation is used for the calculation of Tmrt, we may then expect a determination uncertainty of ±3 K. If all radiative fluxes are modelled based on synoptic observation, the uncertainty in Tmrt is ±5.9 K. Because Tmrt is only one of the four input data required in the calculation of UTCI, the uncertainty in UTCI due to the uncertainty in radiation fluxes is less than ±2 K. The UTCI uncertainties due to uncertainties of the four meteorological input values are not larger than the 6 K reference intervals of the UTCI scale, which means that UTCI may only be wrong by one UTCI scale. This uncertainty may, however, be critical at the two temperature extremes, i.e. under extreme hot or extreme cold conditions.

The thermal environment of the human being on the global scale.

BACKGROUND: The close relationship between human health, performance, well-being and the thermal environment is obvious. Nevertheless, most studies of climate and climate change impacts show amazing shortcomings in the assessment of the environment. Populations living in different climates have different susceptibilities, due to socio-economic reasons, and different customary behavioural adaptations. The global distribution of risks of hazardous thermal exposure has not been analysed before. OBJECTIVE: To produce maps of the baseline and future bioclimate that allows a direct comparison of the differences in the vulnerability of populations to thermal stress across the world. DESIGN: The required climatological data fields are obtained from climate simulations with the global General Circulation Model ECHAM4 in T106-resolution. For the thermo-physiologically relevant assessment of these climate data a complete heat budget model of the human being, the 'Perceived Temperature' procedure has been applied which already comprises adaptation by clothing to a certain degree. Short-term physiological acclimatisation is considered via Health Related Assessment of the Thermal Environment. RESULTS: The global maps 1971-1980 (control run, assumed as baseline climate) show a pattern of thermal stress intensities as frequencies of heat. The heat load for people living in warm-humid climates is the highest. Climate change will lead to clear differences in health-related thermal stress between baseline climate and the future bioclimate 2041-2050 based on the 'business-as-usual' greenhouse gas scenario IS92a. The majority of the world's population will be faced with more frequent and more intense heat strain in spite of an assumed level of acclimatisation. Further adaptation measures are crucial in order to reduce the vulnerability of the populations. CONCLUSIONS: This bioclimatology analysis provides a tool for various questions in climate and climate change impact research. Considerations of regional or local scale require climate simulations with higher resolution. As adaptation is the key term in understanding the role of climate/climate change for human health, performance and well-being, further research in this field is crucial.