The creation of realistic gridded precipitation fields improves our understanding of the observed climate and is necessary for validating climate model output for a wide range of applications. The challenge in trying to represent the highly variable nature of precipitation is to overcome the lack of density of observations in both time and space. Data sets of mean monthly and annual precipitations were developed for Greece in gridded format with an analysis of 30 arcsec (∼800 m) based on data from 1971 to 2000. One hundred and fifty-seven surface stations from two different observation networks were used to cover a satisfactory range of elevations. Station data were homogenized and subjected to quality control to represent changes in meteorological conditions rather than changes in the conditions under which the observations were made. The Meteorological Interpolation based on Surface Homogenized Data Basis (MISH) interpolation method was used to develop data sets that reproduce, as closely as possible, the spatial climate patterns over the region of interest. The main geophysical factors considered for the interpolation of mean monthly precipitation fields were elevation, latitude, incoming solar irradiance, Euclidian distance from the coastline, and land-to-sea percentage. Low precipitation interpolation uncertainties estimated with the cross-validation method provided confidence in the interpolation method. The resulting high-resolution maps give an overall realistic representation of precipitation, especially in fall and winter, with a clear longitudinal dependence on precipitation decreasing from western to eastern continental Greece.

In a series of three companion papers published in this Journal, we identify and validate the available thermal stress indicators (TSIs). In this second paper of the series, we identified the criteria to consider when adopting a TSI to protect individuals who work in the heat, and we weighed their relative importance using a Delphi exercise with 20 experts. Two Delphi iterations were adequate to reach consensus within the expert panel (Cronbach’s α = 0.86) for a set of 17 criteria with varying weights that should be considered when adopting a TSI to protect individuals who work in the heat. These criteria considered physiological parameters such as core/skin/mean body temperature, heart rate, and hydration status, as well as practicality, cost effectiveness, and health guidance issues. The 17 criteria were distributed across three occupational health-and-safety pillars: (i) contribution to improving occupational health (55% of total importance), (ii) mitigation of worker physiological strain (35.5% of total importance), and (iii) cost-effectiveness (9.5% of total importance). Three criteria [(i) relationship of a TSI with core temperature, (ii) having categories indicating the level of heat stress experienced by workers, and (iii) using its heat stress categories to provide recommendations for occupational safety and health] were considered significantly more important when selecting a TSI for protecting individuals who work in the heat, accumulating 37.2 percentage points. These 17 criteria allow the validation and comparison of TSIs that presently exist as well as those that may be developed in the coming years.

Climate variation in temperature describes the fluctuations that occur above or below the average temperature over time. This study focuses on the analysis of various approaches for calculating the average temperature to better capture and represent the true average temperature over the course of a day. As the conventional approach often fails to integrate significant behaviors of temperature variations, nine mathematical formulas are employed with a different number of daily observations. Specifically, this study inserts the geometric and harmonic mean and their variations for the estimation of the average temperature. Furthermore, the application of the formulas to the time series of temperature recordings for three station locations in Greece is analyzed. For the evaluation of the results, six widely used statistical indices for quantifying errors are applied, and their relative effects are also discussed. Finally, as a practical application of the impact of the formula used for the averaging of daily temperature, the various approaches are introduced on the same observation dataset for the estimation of the heating degree-days, an index that can have significant climatological and economic implications over a region.

Background: Specialized occupational health and safety (OHS) issues are covered at the EU level through detailed legislation and guidelines. Unfortunately, this does not extend to occupational heat stress, not only in Greece but also (with few exceptions) internationally. One possible explanation could be the difficulty in accurately identifying the dangerous conditions, as many environmental and individualized elements are involved, and hundreds of "thermal stress indicators" are available. Another explanation could be the difficulty in adequately measuring hazardous conditions for workers affected more (i.e., outdoor and high intensity) since the biological protection framework is based on the human body's internal temperature. Methods: The Wet Bulb Globe Temperature (WBGT) has been proposed as the most efficacious thermal stress indicator. Since 2021, the Hellenic National Meteorological Service has provided 48-h WBGT forecast predictions to serve as a first level of alert. Real-time measurements and 48-h forecasts of WBGT are also available through a smartphone application. Additionally, as revealed when developing the occupational heat stress legislation in Cyprus and Qatar, crucial first steps are identifying the specific characteristics of worker exposure and the tripartite collaboration between employers, workers, and the State. Results: Evaluating the simplified WBGT forecasted values and the smartphone application estimates proved well-established. The sound scientific basis can be effectively combined with administrative measures based on the EU OHS legislative experience to produce practical solutions. Conclusions: As the climate crisis exacerbates, worker productivity and well-being will decline, underscoring the urgent need for an integrated protection framework. Such a framework is proposed here.

Precipitation forecasts provided by high-resolution NWP models have a degree of realism that is very appealing to most users of meteorological data. However, it is a challenge to demonstrate whether or not such forecasts contain more skillful information than their lower resolution counterparts. A verification procedure must be based on equally detailed observations that are also realistic in areas where ground observations are not available and remote sensing data can only increase the accuracy of the location of rain events at the cost of decreased accuracy in estimating the amount of rain that has actually reached the ground. Traditional verification methods based on station or grid point comparison yield poor results for high-resolution fields due to the double penalty error that is attributed to finite space and time displacement that such methods do not account for. A complete approach to evaluating precipitation forecasts over complex terrain is suggested. The method is based on realistic gridded precipitation observations generated by an interpolation method that uses long climate data series to determine the geographical characteristics that this parameter is best correlated with as well as remote sensing estimates as background information to cover the areas where observations are insufficient. Spatial verification methodologies are subsequently applied to a convective event that accentuate the relative skill of high-resolution COSMOGR forecasts in revealing characteristics in the precipitation patterns such as structure and intensity.

Forecasting in-flight icing conditions is crucial for aviation safety, particularly in regions with variable and complex meteorological configurations, such as Greece. Icing accretion onto the aircraft’s surfaces is influenced by the presence of supercooled water in subfreezing environments. This paper outlines a methodology of forecasting icing conditions, with the development of the Icing Potential Algorithm that takes into consideration the meteorological scenarios related to icing accretion, using state-of-the-art Numerical Weather Prediction model results, and forming a fuzzy logic tree based on different membership functions, applied for the first time over Greece. The synoptic situation of an organized low-pressure system passage, with occlusion, cold and warm fronts, over Greece that creates dynamically significant conditions for icing formation was investigated. The sensitivity of the algorithm was revealed upon the precipitation, cloud type and vertical velocity effects. It was shown that the greatest icing intensity is associated with single-layer ice and multi-layer clouds that are comprised of both ice and supercooled water, while convectivity and storm presence lead to also enhancing the icing formation. A qualitative evaluation of the results with satellite, radar and METAR observations was performed, indicating the general agreement of the method mainly with the ground-based observations.