How to find the average temperature in a certain season?

Seasonal average temperature is a climate index, which can provide important information about the climate in a specific area. This information can be used for the following purposes:

Agriculture and Horticulture: Knowing the average seasonal temperature can help farmers and gardeners determine when to plant different crops and plants and when to harvest them. For example, some crops need to grow in a specific temperature range, and if the temperature is too high or too low, it may affect their growth and yield.

Architecture and engineering: The average seasonal temperature can help architects and engineers design buildings and infrastructure to adapt to local climate conditions. For example, in cold areas, buildings need better insulation and heating systems to keep indoor warmth.

Travel and Entertainment: Knowing the average temperature of the season can help people plan their travel and entertainment activities. For example, people may prefer to go to a beach or water park with higher temperature in summer, and they may prefer to go skiing or do other outdoor sports with lower temperature in winter.

Environment and Ecology: Seasonal average temperature can help researchers understand the impact of climate change on the environment and ecosystem. For example, rising temperatures may lead to problems such as melting glaciers, rising sea levels and loss of biodiversity.

Meteorological data such as temperature can be obtained through the meteorological data platform. For example: xi and Energy Big Data Platform (Xihe-Energy)

The first step of the query step: select the geographical location on the home page. You can choose single point data or regional average data.

Step 2: Confirm the data source. What digital sources, European medium-range weather centers and selections can be used for historical data? The forecast data can be selected from the German Meteorological Bureau.

Step 3: Enter the start and end time of the download you want to query. You can choose 40 years of history and 7 days in the future.

Step 4: Select the meteorological data to be downloaded, such as temperature. Export hourly data in csv format and save data visualization pictures.

Step 5: If you need to query more data, you can search for attributes in more attributes.