Data Actuation Using Amazon AWS,NOAA MRMS

The NOAA MRMS data are hosted on Amazon AWS data center publicly. Because these are public data sets, you do not need any account with Amazon to download.

To download this data in your computer from Amazon’s server, you need to download AWS CLI.

You can use python script to download this data, but using AWS CLI is much easier. The CLI stands for Command Line Interface. This software runs on your terminal.

Downloading AWS CLI

Click Here to find all the commands and explanation on how to download Amazon AWS CLI

Microsoft Windows

You can download the .mis file by clicking here

Or you can run the command bellow on your terminal.

msiexec.exe /i https://awscli.amazonaws.com/AWSCLIV2.msi

To check successful installation: aws --version (In Terminal)

Apple Mac

You can download the .pkg file by clicking here

Then run the .pkg file.

To check successful installation: aws --version (In Terminal)

To check location: which aws

Linux

To install the AWS CLI on Linux, run the following commands:

curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install

To check successful installation: aws --version

Subsetting Data & Downloading Using CLI

When using the aws s3 sync command to download data, the command needs to know where on your computer to save the files. The destination folder path.

You have to create a folder. Depending on your operating system the format looks slightly different.

Microsoft Windows Windows

Example 1: Creating a folder on your Desktop

mkdir C:\Users\YourUsername\Desktop\mrms_rain_2025

Example 2: Creating a folder on a secondary drive (e.g., D: drive):

mkdir D:\mrms_rain_2025

Linux / Apple Mac Unix

Example 1: Creating a folder on your Desktop

mkdir -p ~/Desktop/mrms_rain_2025

Example 2: Creating a folder on an external drive or media mount

mkdir -p /media/user/external_drive/rain/2025

You can also create the folder using graphical file explorer (Finder or File Explorer). Then to find the exact command-line path:

Linux/Mac: Drag and drop the folder from finder to the terminal window. The terminal will automatically type out the full path for you (e.g., /Users/name/Desktop/mrms_rain_2025).
Windows: Open the folder in File Explorer, click the address bar at the top, and copy the path (e.g., C:\Users\Student\Documents\mrms_rain_2025).

Putting It Together in the Sync Command

Option A: Using Absolute Path (Recommended)

aws s3 sync \ AWS CLI command for downloading

s3://noaa-mrms-pds/CONUS/PrecipRate_00.00/ \ The remote NOAA AWS S3 bucket source path

YOUR_LOCAL_FOLDER_PATH_HERE \ The absolute path to your local storage folder

--exclude "*" \ Ignores all files in the bucket initially

--include "2025*/**" \ Overrides exclusion to only download folders/files starting with 2025

--no-sign-request \ Bypasses AWS login requirement (for public datasets)

--progress-multiline Displays a multi-line real-time progress bar showing download speed and transferred files

Option B: Using Relative Paths

If you have already navigated inside your destination folder in the terminal using cd, you can use ./ (which stands for “current folder”):

1. Navigate to your target folder first

cd ~/Desktop/mrms_rain_2025

2. Sync directly into the current directory using ./

aws s3 sync s3://noaa-mrms-pds/CONUS/PrecipRate_00.00/ ./ --exclude "*" --include "2025*/**" --no-sign-request

If You Want to Download Only a Few Specific Months

1. Downloading single month (example: August 2025)
Replace --include "2025*/**" with --include "202508*/**"

2. Downloading Multiple Specific months (Example: Aug through Dec)
Use multiple include flags together:

--exclude "*" \
--include "202508*/**" \
--include "202509*/**" \
--include "202510*/**" \
--include "202511*/**" \
--include "202512*/**" \

On Mac and Linux you can write in one line: --include "2025{08,09,10,11,12}*/**"

Multiline works universally across Windows, Mac and Linux

Extracting the Rain mm CSV from .grib2.gz Files

The NOAA MRMS rain data will be in .grib2.gz compress file. It has the rain data for the whole continental US.

You can use python script to extract rain mm. Python

Few Things on the Python Script

NOAA MRMS uses 360 longitude. So, Lehman college: 360 - 73.8945 = 286.1055°

The MRMS calculate the rain in mm/hr. The python script converts it into mm/2min by dividing 30. (Line 89)

Make sure to change the base_path to your local storage folder.