The issue of the quantification of thermal comfort or heat stress on humans is on vogue nowadays. This is evident in the amount of indices or factors, which are trying to quantify these effects. Because of different aims of the development and the complexity of the issue close to 200 thermal indices have been developed and applied for different purposes, in different climate regions and for extreme climate conditions. Most of these indices rely on single meteorological parameters or a combination of them i.e. air temperature and air humidity. In the first half of the twentieth century the necessity of the inclusion of heat budget of the human body arised and in the second half of the twentieth century the first human energy balance models and complex thermal indices have been developed. The complex or rational thermal indices follow the concept of equivalent temperature, which is easier to be understood by users. Most known indices are PMV, PET, modified PET, SET* and UTCI. All the thermal indices require the same thermophysiological and meteorological parameters. For thermophysiology heat production and clothing are required. Air temperature, air humidity, wind speed, as well as short and long wave radiation fluxes in terms of the mean radiant temperature are the required meteorological parameters.

Especially the meteorological factors have to be available in an appropriate spatial and temporal scale depending on the target and the specific issues demanded. The appropriate spatial and temporal resolution data cannot be only delivered by measurement stations. Therefore the collection and availability of different data set is important and complex. Nowadays remote sensing, re-analysis, new techniques of interpolation and climate simulations data can also be used. Modelling issues in the context of human energy balance models and the derived thermal indices, as we as the generation and availability of meteorological data especially in complex topographies and urban areas is required. Meso and micro scale models, which compute not only the meteorological parameters and thermal indices, but also deliver relevant data and information for the climate conditions and can be helpful in the development of mitigation and adaptation strategies in the era of climate change. The main and secondary output can be helpful for different approaches in different disciplines and issues in the context of human health and welfare.

Iran is located in semi-arid and arid parts of the world which often faces water shortage crisis. Hence, monitoring precipitation as a crucial part of the water cycle by accurate methods such as stable isotopes techniques has great importance. Various climatic and geographic parameters influence precipitation in Iran which makes the interoperation of stable isotopes signatures in precipitation very complicated. Thus, sampling stations for stable isotopes analyses in Iran have been classified by cluster analysis (CA) to 10 clusters based on their stable isotope characteristics. The results show that the classification of stations by CA has a close correlation with Koppen climatic zones. For instance, the stations in BWh (hot and arid) zone show the most enriched isotopes values as well as high d-excess, and they exist in four clusters. In these stations, the moisture of precipitation is provided from the Persian Gulf, the Arabian and the Red Seas. These stations also deviate from both Global Meteoric Water Line (GMWL) and Eastern Mediterranean Meteoric Water Line (EMMWL) due to intense evaporation effect on precipitation events. However in stations locate in BSk (semi-arid and cold) zone in three clusters, stations mainly plot on the GMWL. These stations show highly depleted stable isotopes signatures as well as high d-excess values. The precipitation over these stations occur by moisture received from the Caspian and the Mediterranean Seas. Stations in two clusters are located in BWk (cold and arid) zone and they show the highest d-excess values and depleted stable isotopes signatures. Finally, in the last cluster, one station exits and located in Dfb (continental and no dry season) zone. This station shows the most depleted stable isotopes signatures.

The regions of Odesa, Mykolaiv and Kherson, which are located in the southwest of Ukraine and occupy the Northern Black Sea region, have been affected by severe drought occurred in 2019-2020 with catastrophic impact on agriculture sector in 2020.

An overview of the meteorological and synoptic conditions for the formation of this drought showed that the combination of several adverse factors influenced on evolution of drought for a long time.

Analysis of the time course of the drought index SPI on 1 month time scale showed that after relatively favorable spring months at the different points of the Odessa region, the deficit of precipitation (SPI < 0) was observed almost at all months in 2019 (except October), and continued in the first months of 2020.

Analysis of the spatiotemporal distribution of the anomalies of satellite-derived vegetation index NDVI in March-October showed that in 2019, the positive anomalies were observed only in the spring months, but since the beginning of summer and until the middle of the autumn, an increase in the negative anomalies of the NDVI index was observed. March 2020 was characterized by favorable conditions for the vegetation, however, in April, the anomalies of NDVI became negative and reached the minimum in May.

As shown, during months of 2019 in the middle troposphere the monthly positive anomalies of the geopotential heights prevailed in average, which reached maximum values in the second half of 2019 and in January 2020. Analysis of the time course of the ECBI (European continental blocking index) showed that the most prolonged periods of blocking over the European continent were observed in March-April, August-September and November 2019 (from three to six consecutive pentads), as well as in December 2019-January 2020 (four consecutive pentads).

In a series of collaborative Russian-American works (Levina and Montgomery, 2009-2015), we developed and applied an original research approach based on idealized cloud-resolving numerical simulation to quantitatively analyze the self-organization of helical moist convective atmospheric turbulence during tropical cyclogenesis. This allowed us to discover a pre-depression large-scale vortex instability and answer a question “When will cyclogenesis commence given a favorable tropical environment?” The instability emerges against the background of seemingly disorganized convection, in the absence of a visible center of the surface circulation and pronouncedly precedes, from a few hours up to several dozens of hours, the formation of a tropical depression. The onset of instability is diagnosed as the moment when primary (tangential) and secondary (transverse) circulation in the forming hurricane vortex become linked by special convective coherent structures - Vortical Hot Towers (VHTs). The generated linkage makes the nascent vortex an integral mesoscale helical system and ensures a positive feedback between the circulations. The mutual intensification of the primary and secondary circulation begins. The feedback is maintained by convective instability and vortical cloud convection. The forming vortex becomes energy-self-sustaining and intensifying. This can be interpreted as the beginning of a tropical cyclogenesis, while the subsequent formation of a tropical depression / storm may mark the completion of the genesis stage.

In the present work, we focus on the formation of secondary circulation due to close coincidence in time of this process with the onset of instability, and we explore in detail the crucial role of VHTs in both phenomena. The undertaken examination is also intended to contribute to a recently initiated development (Levina, 2020) of early and exact operational diagnosis for the beginning of tropical cyclogenesis based on GOES Imagery and combined with high resolution numerical analysis. The work was supported by the research project “Monitoring” No. 01200200164.

Severe Local Storms (TLS) are considered one of the most dangerous phenomena within the mesoscale. One of its manifestations is strong linear winds, which are known as downbursts, capable of causing great losses to the country's economy and society in general. Knowing which factors in the atmosphere are necessary for the occurrence of this phenomenon is essential for its better understanding and future prediction, which is very complex given the short time of their emergence, development, and dissipation. The objective of the research was to analyze the possible physical factors that accelerate the downdrafts in the storm clouds in Cuba. For this, 10 simulated study cases simulated with the Weather Research and Forecasting (WRF) model at 3 km of the spatial resolution were used. Of these, there were 5 days with reports of downburst and 5 days close to these, both in position and time, in which there was an electrical storm without severity. The factors capable of discriminating between downburst and electrical storms without severity were obtained as the absorption of latent heat by evaporation and fusion, the equivalent potential temperature difference between the level of maximum relative humidity in the low levels and of minimum relative humidity in the middle levels, the speed of the downdraft, and Downstream Available Convective Potential Energy (DCAPE). Unlike previous research, they discriminated against updraft buoyancy and energy advection, both at the middle levels of the troposphere.

This study examined the water budget of Hurricane Irma (2017) through a Lagrangian approach. To identify the moisture sources for the Hurricane Irma genesis and intensification the particle dispersion model FLEXPART was used. The North Atlantic Ocean between 15° and 30° North latitude and the South Atlantic Ocean were identified as the main moisture sources for Irma development. From the perspective of the water budget, the maximum accumulated precipitation along Irma's trajectory coincides with the maximum water budget efficiency, which suggests that total precipitation depends largely on the water vapour supply, rather than the storm intensity. Furthermore, the moisture supplies from the surface under the area delimited by hurricane size is small, thus, the water vapour supplies from the environment through the secondary circulation transports more moisture inward.

^{The main objective of the research is to determine the synoptic and mesoscale conditions that favor the occurrence of locally intense rain in Cuba under the influence of Upper Cold Lows (UCLs). From the outputs of the Rapid Refresh (RAP) model, the characteristics of two UCLs with four cases of locally intense rain associated with them are analyzed. The variables that are studied are: relative humidity, temperature, geopotential height, vertical speed, wind force, divergence, and vorticity. Mesoscale conditions are analyzed using the Weather Research and Forescat System (WRF) model. Vertical cuts, numerical soundings, and analysis of radar observations and satellite images were performed. The CAPE shows extreme values higher than 6000 J/Kg near the center of both systems and the LI reached -13 . The intense rain events develop in an environment of weak vertical wind shear in the surface layer - 500 hPa and moderate to strong in the upper troposphere. High relative humidity values are indentified at low levels, a dry layer at medium levels and an increase in relative humidity at the 300 - 200 hPa layer.}

Ongoing climate variations and variation of winter weather conditions in recent years in Moscow region strongly influence on hill skiing industry. Conducted in the work calculations of possible snow making hours and theirs variations in recent years allows to make conclusions about ongoing changes and possible consequences in future.

An inverse algorithm was developed to profile the vertical structure of temperature and humidity using a feed-forward neural network. Numerous simulations using the inverse algorithm (inverse model) have been conducted and compared with various existing independent techniques. The inverse model is highly efficient at profiling the temperature and humidity vertical structure compared to the existing conventional approaches. The statistical methods notorious for their high computational, altitude-dependent error and inability to retrieve the vertical temperature and humidity profiles are diminished when the inverse model is used. The inverse model’s diurnal and seasonal cycle profiles are also superior to those of other independent existing methods, which may be helpful for assimilation in numerical weather forecast models. We suggest that incorporating such an inverse model into the ground-based microwave radiometer (GMWR) will improve the quality of temperature and humidity profiles and weather forecasting. The developed inverse model has a resolution of 50 meters between the surface to 500 meters and 100 meters between 500-2000 meters, and 500 meters beyond 2000 meters.

Aeroallergen pollen can influence human health, through the response of the immune system, degrading the quality of life. The most common allergic reaction is the hay fever, a highly prevalent and chronic disease, which can affect up to 50% of the population in some cases, especially in the developing countries. Only a moderate number of estimates of the pollen health effects have been made worldwide while in Greece the relevant studies are scarce to non-existing. In Greece one of the most significant taxa are Quercus, but estimations of its pollen concentrations as well its consequent health effects have never been realized before. In this study the potential health effects from Quercus pollen in the greater area of Thessaloniki are estimated. The estimation is implemented with a custom modeling system, comprising the meteorological model WRF, the Natural Emissions Model (NEMO) for the calculation of the Quercus pollen emissions and the chemistry-transport model CAMx for the advection and the deposition of the pollen particles. The period of 2016 with the highest potential is selected, based on the available measurements for the area of interest. The modeling system is evaluated with meteorological and biological measurements, indicating a satisfactory performance on the surface Quercus pollen concentrations. The modeling system is finally utilized for the estimation of exposure levels in the greater area of Thessaloniki.