Google Earth Engine Tutorial: Detect and Visualize Rainfall Anomalies

Credit: Youtube Channel “Terra Spatial, Learn how to detect and visualize rainfall anomalies using climate data for drought and flood monitoring.”

You can see all the tutorials from here: Techgeo Academy.

Google Earth Engine (GEE) offers a powerful platform for analyzing spatial data, including rainfall patterns. Detecting and visualizing rainfall anomalies can help identify areas experiencing unusual precipitation levels, such as droughts or excessive rain. Below is a step-by-step tutorial to achieve this using GEE.

Setting Up the Google Earth Engine Environment

To begin, ensure you have a GEE account and are logged into the platform. Open the GEE Code Editor and load the required datasets for rainfall analysis. Common sources include the Tropical Rainfall Measuring Mission (TRMM) or the Global Precipitation Measurement (GPM) dataset.

Accessing Rainfall Data

Use the ee.ImageCollection function to load historical rainfall data. For example:

var dataset = ee.ImageCollection('NASA/GPM_GeoTIFF/precipitation');
var precipitation = dataset.select('precipitation'); 

This selects the precipitation layer from the dataset. Adjust the parameters to specify the time range and geographic area of interest.

Processing Rainfall Anomalies

Rainfall anomalies are calculated by comparing current rainfall data to historical averages. Follow these steps:

1. Calculate Long-Term Mean: Aggregate historical data for a specific period (e.g., 2000-2020).
2. Compute Standard Deviation: Determine variability in the historical data to establish thresholds for anomalies.
3. Calculate Anomalies: Subtract the long-term mean from the current rainfall image and normalize by the standard deviation.

Example code snippet:

var mean = precipitation.mean(); 
var stdDev = precipitation.reduce(ee.Reducer.stdDev()); 
var anomaly = precipitation.map(function(image) {
  return image.select('precipitation')
    .subtract(mean)
    .divide(stdDev)
    .rename('anomaly'); 
});

Visualizing Rainfall Anomalies

Once anomalies are calculated, use GEE’s mapping functions to display them. Customize the color palette to highlight positive and negative deviations. For instance:

var vizParams = { 
  min: -3, 
  max: 3, 
  palette: ['blue', 'white', 'green'] 
};
Map.addLayer(anomaly.first(), vizParams, 'Rainfall Anomaly'); 

Adjust min and max values to reflect the range of anomalies you want to visualize.

Exporting and Analyzing Results

Export the anomaly data as a GeoTIFF or CSV for further analysis using external GIS tools. Use Export.image.toDrive or Export.table.toDrive functions to save results. Additionally, compute summary statistics to identify regions with significant anomalies.