Utilizing Rainfall and Climate Grid Data Throughout South America

The Brazilian National Institute for Space Research (INPE) offers a wealth of resources for those interested in precipitation and climatological data, specifically for South America. One of the key assets is the MERGE dataset, daily precipitation raster data specifically calibrated for the region.

To begin, you'll need to create a download instance, pointing to INPE's FTP server and setting a local folder where you'll store the files. This is the first step in accessing the data. Once you have the instance set up, the correction and handling of minor issues like CRS definition are taken care of automatically when the assets are opened.

Figure 1 depicts the total precipitation in South America for 2015, showing a large area with a negative anomaly, especially in the Amazon biome, with up to 2,000 mm less rain compared to the previous year. This visualization serves as a testament to the value of these resources, which can be used for various applications such as watershed and reservoir management, monitoring of critical events, and precision agriculture.

The resources provided by INPE are not limited to MERGE. They also offer additional climatological data, including monthly averages and daily averages. Furthermore, the Global Precipitation Measurement mission, which employs a network of satellites to deliver comprehensive global rainfall estimates, complements the data provided by INPE.

Two other globally recognized precipitation datasets are CHIRPS by USGS and IMERGE developed by NASA. The package is compatible with well-established libraries like geopandas and xarray, enhancing its applicability.

The class can automatically create a cube for a given date range, making it easier to analyze data over specific periods. Creating a data cube is advantageous as it consists of several rasters stacked alongside the dimension, allowing for simpler manipulation and analysis. For instance, creating a time series for a particular region can provide valuable insights, especially when considering the rainfall or historical climatology data.

A method to create a data cube with accumulated precipitation for a specific area is to aggregate daily precipitation data spatially and temporally, summing the rainfall values for the specified days within the geographic boundaries. This can be particularly useful for assessing the accumulated precipitation that occurred in a specific region, such as the Amazon biome, over a certain period, like the first half of June 2023.

However, a challenge observed is the intricacies involved in downloading and manipulating these datasets, limiting their use mostly to meteorologists. To address this, an unofficial library called "merge-downloader" has been developed to make it easier to access data from INPE. Additionally, the installation of the Python libraries required for geospatial applications can be simplified using Docker or Google Colab.

In conclusion, the resources offered by INPE, particularly the MERGE dataset, provide valuable insights into precipitation patterns and climatology in South America. With the development of tools like merge-downloader and the use of platforms like Docker and Google Colab, these resources are becoming more accessible to a wider audience, benefiting professionals in various fields, including hydrology and agriculture.