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Reference crop evapotranspiration (ETo) estimations using the FAO Penman-Monteith equation (PM-ETo) require several weather variables that are often not available. Then, ETo may be computed with procedures proposed in FAO56, either using the PM-ETo equation with temperature estimates of actual vapor pressure (ea) and solar radiation (Rs), and default wind speed values (u2), the PMT method, or using the Hargreaves-Samani equation (HS). The accuracy of estimates of daily ea, Rs, and u2 is provided in a companion paper (Paredes et al. 2017) applied to data of 20 locations distributed through eight islands of Azores, thus focusing on humid environments. Both estimation procedures using the PMT method (ETo PMT) and the HS equation (ETo HS) were assessed by statistically comparing their results with those obtained for the PM-ETo with data of the same 20 locations. Results show that both approaches provide for accurate ETo estimations, with RMSE for PMT ranging 0.48-0.73 mm day−1 and for HS varying 0.47-0.86 mm day−1. It was observed that ETo PMT is linearly related with PM-ETo, while non-linearity was observed for ETo HS in weather stations located at high elevation. Impacts of wind were not important for HS but required proper adjustments in the case of PMT. Results show that the PMT approach is more accurate than HS. Moreover, PMT allows the use of observed variables together with estimators of the missing ones, which improves the accuracy of the PMT approach. The preference for the PMT method, fully based upon the PM-ETo equation, is therefore obvious. [ABSTRACT FROM AUTHOR]

This paper deals with the future change projections of extreme cold events in relation to historical climate simulations, based on the comparison between two versions of the GFDL model, CMIP3 and CMIP5, in three regions of southeastern South America where these events are frequent. To this end, the compositions of up to five extreme events below 0 °C at 850 hPa were considered. They were derived from daily data collected from May to September of the NCEP/NCAR reanalysis and GFDL Coupled Atmospheric and Oceanic Global Circulation Model. The study periods run from 1961 to 1990 and from 2081 to 2100 for the most critical scenarios: A2 (GFDL-CM2) and RCP8.5 (GFDL-CM3). Sea level pressure, temperature, and wind were analyzed at 850 hPa and wind also at 250 hPa, for each of the areas under study, representing tropical (Area 1) and subtropical (Area 2 and Area 3) latitudes. The ability of the model to simulate the historical climate, represented by the reanalysis, increased as latitude decreased, CM3 version being better for subtropical latitudes than CM2. Depending on GFDL model version, temperature was higher or lower than those shown by the reanalysis in the tropical latitudes. In contrast, at subtropical latitudes, both versions of the model present lower values. An increase in mean temperature is expected in the future in the three areas, mainly at tropical latitudes (Area 1) according to both versions of the model, which is in line with the results reported by other global models. In Area 2, a further increase in temperature is projected in CM3 version, while, for Area 3, the greatest projection is in CM2 version. Changes are expected for the future climate, primarily explained by the configuration of the circulation fields, such as in the case of the subtropical areas in CM2, whose pattern is more related to that typically associated with radiative cooling, rather than the advective cooling shown in the historical climate. This result is in contrast with the results of the CM3 version, which displays a pattern associated with cold air advection from the south for both the historical and future climate. As regards the tropical area, both versions of the model reveal a considerable reduction in the number of extreme cold events. [ABSTRACT FROM AUTHOR]

This paper analyses winter severity and snow conditions in the Karkonosze Mountains and Jizera Mountains and examines their long-term trends. The analysis used modified comprehensive winter snowiness (WSW) and winter severity (WOW) indices as defined by Paczos (1982). An attempt was also made to determine the relationship between the WSW and WOW indices. Measurement data were obtained from eight stations operated by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB), from eight stations operated by the Czech Hydrological and Meteorological Institute (CHMI) and also from the Meteorological Observatory of the University of Wrocław (UWr) on Mount Szrenica. Essentially, the study covered the period from 1961 to 2015. In some cases, however, the period analysed was shorter due to the limited availability of data, which was conditioned, inter alia, by the period of operation of the station in question, and its type.Viewed on a macroscale, snow conditions in the Karkonosze Mountains and Jizera Mountains (in similar altitude zones) are clearly more favourable on southern slopes than on northern ones. In the study area, negative trends have been observed with respect to both the WSW and WOW indices—winters have become less snowy and warmer. The correlation between the WOW and WSW indices is positive. At stations with northern macroexposure, WOW and WSW show greater correlation than at ones with southern macroexposure. This relationship is the weakest for stations that are situated in the upper ranges (Mount Śnieżka and Mount Szrenica). [ABSTRACT FROM AUTHOR]

The present paper reports a study, where growing hierarchical self-organising map (GHSOM) has been applied to achieve a visual cluster analysis to the Indian rainfall dataset consisting of 142 years of Indian rainfall data so that the yearly rainfall can be segregated into small groups to visualise the pattern of clustering behaviour of yearly rainfall due to changes in monthly rainfall for each year. Also, through support vector machine (SVM), it has been observed that generation of clusters impacts positively on the prediction of the Indian summer monsoon rainfall. Results have been presented through statistical and graphical analyses. [ABSTRACT FROM AUTHOR]

Estimating the ultraviolet-B (UV-B) solar irradiance and its angular distribution is a matter of interest to both research and commercial institutes. A static multi-sensor instrument is developed in this paper for a simultaneous measuring of the sky and the reflected erythemally weighted UV-B irradiance on multiple inclined surfaces. The instrument employs a pre-developed simple solar irradiance model and a minimum mean square error method to estimate the various irradiance parameters. The multi-sensor instrument comprises a spherical shaped apparatus with the UV-B sensors mounted as follows: seven sky-facing sensors to measure the hemispherical sky irradiance and six sensors facing downwards to measure the reflection from ground. This work aims to devise and outline an elementary, low-cost multi-sensor instrument. The sensor may usefully serve research, commercial, and medical institutes to sample and measure the UV-B irradiance on horizontal as well as on inclined surfaces. The various UV-B calculations for inclined surfaces are aided by the sensor's integrated software. [ABSTRACT FROM AUTHOR]

Soil temperature is an important factor within the climate system. Changes of trends in soil temperature and analysis of vulnerability due to heat stress can provide useful information on climate change. In this paper, the soil temperature regime was analyzed on seasonal and annual scales at depths of 2, 5, 10, 20, 30, and 50 cm at 26 sites in Croatia. Trends of maximal, mean, and minimal soil temperatures were analyzed in the periods 1961-2010 and 1981-2010. Duration of extreme soil temperatures and vulnerability due to high or low soil temperatures in the recent standard period 1981-2010 was compared with the reference climate period 1961-1990. The results show a general warming in all seasons and depths for maximal and mean temperatures in both observed periods, while only at some locations for minimal soil temperature. Warming is more pronounced in the eastern and coastal parts of Croatia in the surface layers, especially in the spring and summer season in the second period. Significant trends of maximal, minimal, and mean soil temperature in both observed periods range from 2.3 to 6.6 °C/decade, from −1.0 to 1.3 °C/decade, and from 0.1 to 2.5 °C/decade, respectively. The highest vulnerability due to heat stress at 35 °C is noted in the upper soil layers of the coastal area in both observed periods. The mountainous and northwestern parts of Croatia at surface soil layers are the most vulnerable due to low soil temperature below 0 °C. Vulnerability due to high or low soil temperature decreases with depth. [ABSTRACT FROM AUTHOR]

This paper examines the potential for the use of artificial neural networks (ANNs) to estimate the reference crop evapotranspiration (ET0) based on air temperature data under humid subtropical conditions on the southern coast of the Caspian Sea situated in the north of Iran. The input variables for the networks were the maximum and minimum air temperature and extraterrestrial radiation. The temperature data were obtained from eight meteorological stations with a range of latitude, longitude, and elevation throughout the study area. A comparison of the estimates provided by the ANNs and by Hargreaves equation was also conducted. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two approaches. The results of this study showed that ANNs using air temperature data successfully estimated the daily ET0 and that the ANNs with an R2 of 0.95 and a root mean square error (RMSE) of 0.41 mm day−1 simulated ET0 better than the Hargreaves equation, which had an R2 of 0.91 and a RMSE of 0.51 mm day−1. [ABSTRACT FROM AUTHOR]