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Meteo Satellite

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meteoblue uses real time satellite data from different providers and merges them to a global composite, that is available within our weather maps plugin and the tile API. Furthermore, the data is used for cloud nowcasting.



meteo satellite

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meteoblue uses radar data from different providers and merges them to regional composites, that are available within our weather maps plugin and the tile API. Furthermore, the data is used for precipitation nowcasting.


Satellite data is available from the geostationary satellites GOES-16/17, Meteosat-8/11 and Himawari-8. The spatial resolution varies between 1 and 3 kilometers at the equator below the satellite. Images are available every 10 respectively 15 minutes depending on the source.


The Normalised Difference Vegetation Index (NDVI) is a satellite product which indicates vegetation greenness. It is calculated as a normalised ratio between the red and near infrared satellite channels. The NDVI varies between 0 and 1, with a value close to 1 indicating high vegetation greenness and hence high vegetation density and health.


A clever combination of satellite images at certain wavelengths into an RGB can highlight low clouds and fog as well as distinguish them from one another. Two such RGB composite images queried by the following parameters:






MeteoSwiss obtains the satellite data from EUMETSAT, a consortium of European countries which together operate METEOSAT and other Earth observation satellites. The weather satellites transmit images in various different light frequency ranges.


MeteoSwiss publishes four different satellite images: a high-resolution daytime image of Switzerland and neighbouring regions, a combined day-and-night image of Europe, an infrared image of Europe and a satellite image of the world. The data can be displayed in real time and in time lapse (with measurements from the last few hours). Explanations of the various satellite images are displayed automatically.


The device has two cameras for remote sensing of the Earth. They will make it possible to obtain images for monitoring oil and oil product spills in the Arctic zone, as well as to predict the development of the situation on the Northern Sea Route, to identify the formation of dangerous meteorological phenomena.


The satellite images show most of the currently existing clouds. However, small clouds, fog, clouds at night and aerosols are not necessarily visible. High clouds and clouds with vertical development are displayed in white, low clouds and fog in grey. In mountainous areas, snow is sometimes erroneously classified as clouds.


Infrared satellite telemetry is used to calculate the temperature of the clouds. Low clouds and fog are difficult to distinguish from ground temperatures and might therefore be inaccurately identified in places where cloud and ground temperatures are similar.


Infoplaza is one of the largest all-round meteorological service providers for media, consumers, governments, and businesses. Additionally, Infoplaza has a mobility division for public transport and traffic information.


The map above depicts a satellite-based estimate of rainfall rates (in millimeters per hour) over Greece for September 6, as heavy rain continued. The darkest reds reflect the highest rainfall rates, which again hit central Greece as well as areas to the south, including Athens. The data are remotely sensed estimates that come from the Integrated Multi-Satellite Retrievals for GPM (IMERG), a product of the Global Precipitation Measurement (GPM) satellite mission. Due to averaging of the satellite data, local rainfall rates may be significantly higher when measured from the ground.


Thanks to this feature, Meteonorm now offers access to all relevant meteorological information required for planning of solar applications through the same software platform: typical years, monthly averages, hourly time series.


The database consists of more than 8 000 weather stations, five geostationary satellites and a globally calibrated aerosol climatology. On this basis, sophisticated interpolation models, based on more than 30 years of experience, provide results with high accuracy worldwide.


In this context, satellites have become a valuable source for solar irradiation data, in particular in areas with sparse distribution of met stations. However, this approach also includes disadvantages such as lack of other meteorological parameters, uncertainties in aerosol values, detection of multiple cloud layers, inaccuracies in areas with snow or no data north of 62.


There is no standard rule which option is the best one. We always recommend combining multiple data sources of ground and satellite data to achieve the lowest uncertainty for resource assessment. Meteonorm includes weather stations and satellite data


Xylella fastidiosa subsp. pauca (Xfp), has attacked the olive trees in Southern Italy with severe impacts on the olive agro-ecosystem. To reduce both the Xfp cell concentration and the disease symptom, a bio-fertilizer restoration technique has been used. Our study applied multi-resolution satellite data to evaluate the effectiveness of such technique at both field and tree scale. For field scale, a time series of High Resolution (HR) Sentinel-2 images, acquired in the months of July and August from 2015 to 2020, was employed. First, four spectral indices from treated and untreated fields were compared. Then, their trends were correlated to meteo-events. For tree-scale, Very High Resolution (VHR) Pléiades images were selected at the closest dates of the Sentinel-2 data to investigate the response to treatments of each different cultivar. All indices from HR and VHR images were higher in treated fields than in those untreated. The analysis of VHR indices revealed that Oliarola Salentina can respond better to treatments than Leccino and Cellina cultivars. All findings were in agreement with in-field PCR results. Hence, HR data could be used to evaluate plant conditions at field level after treatments, while VHR imagery could be used to optimize treatment doses per cultivar.


When analysing spectral vegetation index values from satellite images, changes in the indices selected may be related to several causes, including vegetation soil coverage, pruning dates, reduced rain events, heat waves29. Thus, pruning dates are reported in Table 1, for each experimental field, to identify possible decreases in the spectral values due to tree biomass reduction after pruning (first subsection). Rain and temperature values were collected in the study period (second subsection). Finally, to minimize the background spectral contribution, only satellite images acquired in July and August were analysed. Actually, during these months, the vegetated background is generally dry in Salento (third subsection).


Daily maximum temperature values are plotted from March to June, for the years 2013, 2019 and 2020 in Fig. 3. This Figure shows that the Ionian coast experienced higher temperature values (Fig. 3a) than the Adriatic coast (Fig. 3b). This occurrence was more evident in May and June, 2019 and 2020. On the Ionian coast, the mean month temperature was about 23, but the meteo-station registered temperatures higher than 30 for three consecutive days in May 2020. The black circle in Fig. 3a, third line, shows the heat wave.


The additional analysis carried out for Nardò A and Nardò B treated fields, close to the Nardò meteo-station, is reported in Fig. 13a, b. The findings from these two fields confirm that after treatments, the NDVI values from treated trees, remained higher than those from untreated ones. Even though Pléiades images were not atmospherically corrected, the NDVI trends from Pléiades were compatible with those obtained from S-2, for all the study areas.


The present paper discusses an application of multi-resolution satellite data to evaluate the effectiveness of a restoration action in olive groves affected by Xfp in Salento, Apulia Southern Italy. Restoration actions of olive agro-ecosystems are of critical importance for the entire Mediterranean basin, not only for supporting local economies but also to increase the area resilience to climate changes. The number of studies demonstrating that olive agro-ecosystem can reduce net emissions of greenhouse gases and land degradation processes has been expanding in recent years15,19,39,40,41. These studies appear to justify the efforts for recovery actions of olive groves affected by Xfp in the Mediterranean area.


To evaluate how long it had taken for trees to respond to treatments, as well as to evidence the possible impact of meteo-events on the spectral index trends, the yearly time-series was also analysed. The findings (Figs. 6 and 7) revealed that in all treated fields investigated, all spectral index values started to increase after two years from the beginning of the treatments with the bio-fertilizer. For the Cannole and Galatone areas, the values for treated fields with respect to their neighbour untreated ones were found to be similar in the years when the treatments had started (2016 and 2017, respectively). In addition, the drought event occurred in 2017 may have slowed down plant recovery (Fig. 6). Following almost two years of tree treatments, the NDVI, OSAVI, NDRE and ARVI index values of the trees resulted higher than the untreated ones. After three years of treatments, the yield of all olive trees (Ogliarola Salentina, Leccino and Cellina di Nardò) was the same as the one obtained before the Xfp epidemic, i.e., 25-30 q.ls/ha23.

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Meteo Satellite Phillipa Stricklan <phillipastricklan@gmail.com> - 2024-01-03 04:11 -0800

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