AWS Metadata Report Preparation
AWS Metadata Report Preparation
Monthly AWS Data Download
ü At the end of each month, we download Ambient Weather Station (AWS) data from AmbientWeather.net (AWN) website. (email and password to access the website will be provided.)
Figure 1: ambientweather.net website
ü When you first visit the website, click on the “Log in” option located at the top-right corner of the page. Log in using the username and password provided to you.
ü After logging in, navigate to “My Dashboard.”
Figure 2: ambientweather.net dashboard
ü In the ‘My Stations’ section at the top center of the page, you will see a drop-down menu.
ü Click on the drop-down menu to view the working status of all stations.
Figure 3: Working status of ambient weather stations
ü Click on each station that was operational during the previous month. For example, let’s consider the Digana station.
Figure 4: Graphs and tables of AWS data
ü After selecting each station, follow the steps indicated by the arrows in the order shown.
ü When you reach Step 3, you will be prompted to select the date range for downloading the data. Typically, the previous month’s dates are selected — for example, from 01.09.2025 to 30.09.2025.
ü Enter the start date in the first calendar and the end date in the second calendar.
Figure 5: Selection of the date range to download data
ü After selecting the date range, click ‘Apply’.
ü When you scroll down, you can see all the available data within the selected time period.
Figure 6: Available data from the selected date range
ü After choosing the date range, click on the button indicated by the arrow.
ü In the pop-up box that appears, select the ‘Export All Data’ option to download the dataset.
ü Once all the above steps are completed, the available data for the Digana station during the selected period will be downloaded to your computer.
ü Rename the file appropriately and repeat the same process for each station that was operational during the selected period.
ü Once all the data for all functioning stations are downloaded, store them in Met_Data_2025 Gdrive folder organized by station and month (access to this Gdrive folder should be requested).
ü After downloading data, we prepare a meta data report for each station.
ü To generate the meta data reports, we run a Python-based script in GitHub. (email and the password to access the repository will be provided.)
ü After logging in, navigate to ‘Metdata04/metadata_model’ repository.
Figure 7: 'Metdata model' repository
ü Let’s once again take Digana station as an example to prepare the AWS Metadata Report.
ü Click on the ‘vercel’ link located at the top right corner.
ü This link will take you to the following interface.
Figure 8: Generating the metadata report
ü Click on ‘Choose file’ and upload the previously downloaded Digana station data file.
ü Once the file is uploaded, select ‘Generate Report’ to proceed.
ü Once the metadata report has been generated, a message saying ‘The report is generated’ will appear.
ü When the above message is displayed, go back to the repository and refresh.
ü After refreshing the repository, open the ‘metadata reports’ folder.
ü You will find all previously generated metadata reports listed there.
ü Locate and download the Digana metadata report you just created as a .csv file.
ü Use the ‘Download’ button in the top right corner, above the table, to download the metadata report as a .csv file.
Figure 9: Downloading the metadata report
ü Save the metadata reports in the folder named Met_Data_2025 (organized by year and month).
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