NOAA Satellite Images

How neat would it be to get satellite weather images straight from the satellite to your house? It’s not that difficult or expensive. You can do it with a homemade dipole antenna, a Software Defined Radio (SDR) , a Raspberry Pi (microcomputer), and some software.

NOAA has three satellites: NOAA 15, NOOA 18 and NOAA 19, and Russia has the METEOR-M 2 one that are on a polar orbit and fly over Anchorage at about the same time every day. The NOAA satellites transmit Automatic Picture Transmission (APT) formatted images near 137 MHz. Like almost anything in ham radio, there are at least a dozen different ways to do anything.

According to Wikipedia, APT images from weather satellites can be received with a right-hand circular polarized, 137 MHz antenna. The two most frequently recommended antennas are the crossed dipole and the quadrifilar helix antenna (QHA or QFH), but I went with a homemade 137 MHz dipole antenna that I clamped to a deck railing.

There are lots of examples on the internet. The dipole legs are about 21 inches long, and join at the center at a 120 degree angle. The legs are zip tied to a scrap of laminate flooring. The “V” shape is horizontal. The weird part is where some of them jump between scientific reasoning and then rumors. Some web sites will include a pair of NEC simulations that shows that the 120 degree angle make the antenna omni-directional. After proving that the antenna is omni-directional, they will tell you to point the “V” to the north!?


I went with brand name “Nooelec” SDR and a combination filter and Low Noise Amplifier (LNA). The LNA is outside by the antenna, and is powered by the SDR over the transmission line. Much easier than messing around with running power out to the antenna.

Nooelec NESDR SMArTee XTR SDR – Premium RTL-SDR w/Extended Tuning Range, Aluminum Enclosure, Bias Tee, 0.5PPM TCXO, SMA Input. RTL2832U

Raspberry Pi 4 – 1 GB The printed circuit board is the size of a credit card. In March of 2022 these are out of stock all over the world.

Nooelec SAWbird+ NOAA – Premium Saw Filter & Cascaded Ultra-Low Noise LNA Module for NOAA Applications. 137MHz Center Frequency

Software and Setup

It wasn’t a simple download and everything magically works. It took some futzing around to get things working. At first I tried the “quick start” that started with loading a current copy of the Raspberry Pi operating system, then loading the Raspberry NOAA V2 software. Since the instructions were written, one of the packages changed to a higher version. The higher version package is missing a sub-package that was in the older version. I tried a bunch of stuff, and couldn’t get it to run.

I ended up using a pre-packaged image from It’s got the operating system and all the NOAA V2 stuff in one convenient image that you reload your memory card with. The software appeared to run. I could see the schedule for the satellite passes, and after they went over, I saw a bunch of Alaska maps with noise all over them.

I went outside in the snow, cold and wind to look at the antenna. Did you know that you can buy SMA cable adapters that have the correct mechanical threading on them, but the opposite electric connections? It turned out I had no center pin connection at all.

I started getting some partial, fuzzy satellite images. So when you see recommendations for a crossed dipole or a quadrifilar helix antenna and you are only running a dipole, you should crank the gain up, right? No, you shouldn’t crank the gain up as high as it goes. Crank the gain and you crank the noise all the way up too. I started with a gain of 42.0, and I’m now down to 9.0.

NOAA-15 – 2022-02-27 at 9:38 AM

The Raspberry Pi runs a web server with a satellite images page that the RaspiNOAA software updates. For this pass of the NOAA-15 satellite there is a thumbnail image like this.

This is what the pass looked like.
Spectrograph of the pass. The received signal really kicked in at 337 seconds and faded around 607 seconds.
The audio file processed into an image. The image is 2080 pixels wide. On the left is the visible image, near sunrise. The right side is the infrared image.
This is the MCIR processing of the image. The location of the satellite is know, so we can insert the map and lat/lon lines. The legend box at the top is generated and overlaid on the image. MCIR Colours the NOAA sensor 4 IR image using a map to colour the sea blue and land green. High clouds appear white, lower clouds gray or land/sea coloured, clouds generally appear lighter, but distinguishing between land/sea and low cloud may be difficult. Darker colours indicate warmer regions.
MSA precip processing. The software can highlight the precipitation based on IR temperature.

My house is to the South, and behind that, I’ve got a ridge that blocks the bottom 20 to 26 degrees of the horizon (elevation) and is about 90 degrees wide (azimuth). Also have some spruce trees to the North. On a clear day I can see 135 miles to Denali, so that make up for the ridge to the South.

The images are pretty neat. These are relatively low resolution images. It’s the equivalent of analog TV in an age of digital 4K HDR 120 Hz images. The NOAA satellites transmit using Automatic Picture Transmission (APT), which was developed in the 1960s.

The satellites image is visible and infrared. It comes across as audio. The software has over a dozen different options for processing the images.


The Meteor satellites were launched by Russia. The METEOR-M 2 transmits on 137.10 MHz in a different format than the NOAA satellites. My experience has been more miss than hit, but when you get a good pass, it is in a much higher resolution and is a beautiful image.

The above image at full resolution, cropped around Cook Inlet.

Walter Yankauskas – KL7WY – 2022-03-01