This master's thesis analyses and forecasts the impact of climate change in the production of wine in the region of Bordeaux, taking into consideration many different indicators that measure the quality of the wine.

The historical weather data was retrieved from history+ for 3 different locations in the region. Hourly data for variables such as air and soil temperatures, radiation, precipitation and more were used for the analysis.

In order to forecast malaria incidence in Senegal, this research paper created a generalised model using as input data of climatic variables (specifically precipitation), the history of malaria's occurrence, and more.

Historical datasets from 2008 to 2016 were retrieved and analysed using the meteoblue history+ interface. Precipitation, humidity and temperature historical data were the variables relevant to support the generation of the model.

This paper assesses the usage of heat pumps as an alternative for heat supply in Ukraine. The research also uses climatic conditions as input, as well as energy specifications of the country, and the engineering aspects of heat load systems.

The study used historical data for the city of Kiev, available on the meteoblue history+ interface. Variables such as air temperature, wind speed, solar radiation, and precipitation were relevant to support the research conducted in this study.

Applying machine learning models, this master's thesis aims to develop a high accuracy prediction model for precipitation events.

Historical rainfall weather data simulation has been retrieved from history+, and contributed utilised in to the studies, and served as a basis to the development of the model for Taunggyi.

The goal of this paper is to gather evidence to correlate the volume of illegal migrants from Mexico to the US, taking into account climate change effects on agricultural production and seasonal patterns of temperature and precipitation.

35 years of historical data provided by meteoblue were analysed, and enabled the detection of weather-migration patterns related to temperature and precipitation in different locations in Mexico.

Focused on determining the impacts of climate change on the rice production in Italy, this project gathers different data of climate and agriculture, and detects correlations to the impacts.

The high-resolution historical data, starting from 2008, provided by meteoblue was used to better understand the climate characteristics of the weather for the regions of Piedmont and Lombardy.

In order to improve the efficiency of wheat production in Pakistan, this research examines the usage of remote sensing and machine learning technologies in the planning and operational activities in the field.

Historical meteorological data for the region of Faisalabad, Pakistan (retrieved via the meteoblue history+) was used as input for the calculation of wheat yield predictions in this research.

Considering the effects of climate change this study analyses the correlation between the changing temperatures, tourism behaviour and skiing activities on the Garmisch-Partenkirchen area, since 1920.

Temperature and snowfall amount data were used to analyse the direct impact of weather conditions throughout the years. The history+ database provided historical data from 1985 for this paper.

As part of the process of location selection for the installation of wind turbines in the region of Luzon, Philippines, this paper examines the important criteria for an offshore wind farm, such as weather conditions, financial and logistic plans.

Wind speed data was the most important weather variable required for this study. meteoblue historical weather simulation data was obtained for a period of more than 35 years (1985- 2021).

The goal of this study is to examine and evaluate the various outputs of a water temperature model utilising several meteorological data sources as input. The South Saskatchewan River was chosen as the study's focal point.

One of the meteorological datasets used as input came from the meteoblue historical weather simulation database. In the study, this dataset was compared to 2 other datasets, and the outcomes confirmed its high accuracy and usability.

With the goal of obtaining better understanding the correlation between climate change and the geography of Italy (specifically in mountains and valleys), this study uses an algorithm that was developed to estimate the ruggedness of certain areas and analysing their warming rates.

More than 30 years of meteoblue historical weather simulation data were assessed (from 1985 to 2018), in hourly time steps. The data was used to calculate annual average temperature and detect potential anomalies.

The goal of this research was to determine the effects of climate change on the operating capacity of transmission lines in Brazilian wind farms, assuring the lines' dependability.

meteoblue historical weather simulated data of 7 years (2014-2021) contributed to the study, with variables such as wind speed and ambient temperature being analysed for 3 coordinates where transmission lines were located.

The goal of this research is to learn more about the impact of climate change on debris-covered glaciers as compared to clean ice glaciers, as well as the varied spatial and temporal consequences that the debris cover exerts.

30 years (1990-2020) of historical weather simulation data for three glacier locations (Miage, Himal Chuli and Hinang Glacier) were obtained, to observe the local development of the average temperature and snowfall amount.

This study aimed to increase the understanding of the functioning of the ecological system of the “Gelaagpark” and its vegetation, geography, and wildlife species.

The meteoblue historical data was used to support the study in terms of the climatic factors applicable to this area, such as temperature, precipitation, wind and air humidity. The extent of the analysed period was 20 years (2000-2020).

In the context of renewable energy, this study approaches the topic of energy autonomy of island areas with the aim to determine to what extent it is possible for the island of Corsica, France, to be self-sufficient in electrical energy.

Historical weather data provided by meteoblue was used to retrieve wind speed data at 80m height between 2015 and 2020 on three sites of Corsica, supporting the estimation of energy produced by wind turbines.

The focus of the study was to learn more about the reef manta ray species, their habitat, and the environmental factors that impact their behaviour. This is part of an effort to create a reef manta ray conservation management strategy.

The meteoblue historical weather data was used to assess the impact of wind speed and direction on the manta ray behaviour and habitat.

This research aims to better understand cloud science in order to construct a real-time weather rendering system that can be utilized to produce high-accuracy weather simulations for application in games and other purposes.

meteoblue weather data was used to visualise past, current and forecast data. Most importantly cloud coverage data of different atmosphere layers, but also precipitation and wind data.

Targeting the optimisation of the charging process of electric vehicles, this master thesis develops an algorithm that takes into consideration aspects such as fluctuation of grid usage fees and the economic potential of different combinations of renewable sources.

The algorithm used historical solar power production data from meteoblue, which contains historical data of solar power production based on kilowatt peak, to calculate the energy generation outputs.

The effects of climate change on commercial activity in mountain locations were examined in this master's thesis. Seasonal effects, climate change mitigation methods, and sustainable development activities were considered.

The meteoblue historical weather simulation data was mainly used to analyse the climatic development during winter seasons, observing weather variables such as temperature, relative humidity, snowfall amount, and more.

This study aims to contribute to the project of infrastructural and social rehabilitation of the city of Mosul, Iraq, where large scale armed conflicts took place in 2017, leaving behind a trace of destruction.

To optimise the construction and architecture initiatives in the region, understanding the region's climatic characteristics is a key aspect. The meteoblue historical weather simulation data was obtained for the city of Mosul and was used to support the studies.

Approaching the topic of renewable energies, this study evaluates the adoption of a hybrid renewable energy system to determine the best energy mix. The Canary Islands were chosen as the site for a case study.

The meteoblue history+ was used to retrieve wind data in the form of wind roses and histograms.

The purpose of this master's thesis was to build an efficient technique for rice yield prediction in Colombia, utilising a machine learning approach in order to solve the potential problem of regional food supply induced by climate change.

The meteoblue historical weather simulation data was used as source for multiple weather variables such as precipitation, temperature, relative humidity, sunlight hours and more.

This study highlights the importance of wind data as validation for the implementation of wind farms in developing African countries. A major barrier for the development of renewable energies in development countries is the paucity of available relevant information.

The study is based on the meteoblue historical wind speed and direction data from 2011 to 2016 for 4 locations in Cameroon and Nigeria.

As part of the design project of the “Attranyon”, an innovative commercial building in Switzerland, this study assesses the energy consumption and self-sufficiency aspects for the project. It is meant to serve as a model project for Switzerland to follow in order to meet its climate goals.

The last 10 years (2010-2020) of temperature data were obtained from the meteoblue historical weather simulation database, and used as part of the calculation of the building's energy consumption.

In the context of Covid-19, this study analyses the impact of the lockdown measures on the transportation and industry related emissions, particularly in the cities of Pisa, Lucca and Florence, in Italy.

To examine the potential impacts of the decreased emissions, weather data from the meteoblue historical weather simulation database was obtained. Variables such as wind speed, precipitation, relative humidity and more were retrieved for the three aforementioned cities.

The aim of the research is to obtain better understanding of the severely endangered lemur leaf frog. Understanding the species' behaviour, breeding, and nesting in relation to the weather and to moon phases might contribute to the establishing of conservation measures.

As a part of the paper's weather analysis, hourly data for humidity, air temperature, and cloud cover were retrieved for the region of Limon, Costa Rica, from the meteoblue historical weather simulation database.

This study's focus was to develop a photovoltaic power forecasting mechanism based on a machine learning model (directly impacted by many meteorological factors in the context of renewable energy) and addressing the estimation of solar power output.

In this study, more than 30 years of meteoblue weather simulation data were used as input for the machine learning models. Specifically, air temperature, relative humidity, cloud cover, shortwave radiation, wind speed, and direction.

This study analyses the development of Agricultural Photovoltaic Systems, a method that allows the same piece of land to be used for agriculture and photovoltaic energy production at the same time.

The meteoblue historical weather data was used to assess the productivity of photovoltaic energy generation systems. Weather variables such as air temperature, relative humidity and solar radiation were obtained for locations in Germany, Spain and Turkey.

Assessing the correlation between the weather conditions and beer sales volume in Denver, United States of America, this study gathered data from breweries and restaurants as well as the weather of different seasons, aiming to better understand beer consumption patterns.

The mean temperature, precipitation and sunshine hours were the variables analysed in this study, and that were taken from the meteoblue historical weather simulation database.

As part of a plan to reduce electricity costs and CO₂ emissions in the campus of Queen Mary University, this project will assess the feasibility of implementing a wind turbine as energy supply. A Computational Fluid Dynamics simulation was performed to understand the wind behaviour, and different types of turbines were tested.

The meteoblue historical weather simulation data were used to study the wind speed and direction development at the Queen Mary campus. A wind rose was also used in the project to assess and demonstrate the wind distribution.

In order to apply the concept of Finite Sample Smeariness (FSS) in a real use case, the study used wind data as subject for test and analysis, using bootstrap tests and measuring its efficiency.

20 years of wind direction data (2000-2019) of Basel and Göttingen were used to detect a potential changing pattern that could indicate effects of climate change.

This study uses statistical analysis of the linear trends of maximum and minimum temperature, as well as seasonal trends, in order to improve the understanding of the climate in Lahore, Pakistan.

The development of temperature trends was calculated using 31 years of the meteoblue historical weather simulation data (1988-2019). The data has been subjected to statistical analysis, and contributed to the study's findings.

The aim of this study was to collect air pollutant measurements, as well as the utilisation of meteorological and traffic data, in order to better understand the air quality situation in Paris, and finally to create a map of air pollution.

Weather variables such as wind, precipitation and temperature were retrieved from the meteoblue weather simulation database, contributing to the meteorological analysis of the project.

This bachelor's paper aimed to analyse the situation of table grapes in Germany (one of the most consumed fruits there), which saw its harvesting activities neglected by local farmers, leading to a large need for imports.

To understand if the weather conditions are a key barrier for harvesting the table grape in Germany, the meteooblue weather data from 1985 to 2019 was analysed. Variables such as temperature, precipitation, and sunshine hours were obtained for the analysis.

Considering the effects of climate change, this study analyses the impacts of extreme weather events and changing temperatures in the operation of airports. Furthermore, the study provides options for mitigation measures to be applied, taking the weather variables analysis into consideration.

Wind speed and direction data of the last 35 years (including wind roses and diagrams) were provided by meteoblue and used as input to study three Canadian airports' locations.