Group for Earth Observation

No 72 - December 2021

This image, captured by the Copernicus Sentinel-2 mission on October 10, 2021, shows a new flow of lava
from the Cumbre Vieja volcano erupting on the Spanish island of La Palma. The image has been processedin true colour, using the shortwave infrared channel to highlight the lava flow.
Image: ESA

Useful User Groups

GEO MANAGEMENT TEAM
General Information
John Tellick,email: information@geo-web.org.uk

GEO Newsletter Editor
Les Hamilton,
email: geoeditor@geo-web.org.uk

Technical Consultant (Hardware)David Simmons
email: tech@geo-web.org.uk

Webmaster and Website Matters

Weather Satellite Reports
This group provided weekly reports, updates and news
on the operational aspects of weather satellites.

https://groups.io/g/weather-satellite-reports

SatSignal
This end-user self help group is for users of David
Taylor’s Satellite Software Tools, including the orbit
predictor WXtrack, the file decoders GeoSatSignal and
SatSignal, the HRPT Reader program, the remapper
GroundMap, and the manager programs - MSG DataManager, GOES-ABI Manager, AVHRR Manager etc.

https://groups.io/g/SatSignal

Vacancye-mail: webmaster@geo-web.org.uk

Management TeamDavid Anderson
Rob Denton

MSG-1
This forum provides a dedicated area for sharing
information about hardware and software for receiving
and processing EUMETCast data.

https://groups.io/g/MSG-1

Nigel Evans: nigel.m0nde@gmail.com
Clive Finnis
Carol FinnisPeter GreenDavid SimmonsDavid Taylor

GEO-Subscribers
This is the official group is for subscribers of the Groupfor Earth Observation (GEO), aimed at enthusiasts
wishing to exchange information relating to either GEO
or Earth Observation satellites.

https://groups.io/g/GEO-Subscribers/

Tiger
www.geo-web.org.uk

2

Les HamiltonThanks to welcome contributions from several readers, we have a super 40+
page edition of the Newsletter for you this quarter. There are two offerings from
Ed Murashie, one describing the Sally Ride EarthKAM, which is mounted on theInternational Space Station. Ed explains how you can book time slots to image yourchosen region of the planet using it. Secondly, Ed embarks on the ﬁrst part of a triple
feature on the Landsat series of satellites, in this issue detailing how they came tofruition.

R

ichard Fairman describes how he overlays Met Ofﬁce charts upon Meteor M2
imagery while Richard Osborne writes about visualising of EUMETCast SAF
products. There’s also an interesting update about the continued progress of theDundee Satellite Station from Neil Lonie.

The startling cover image on this issue relates to the ongoing eruption of the Cumbre
Vieja volcano on the island of La Palma in the Canaries. At the time of publication,
the eruption had been ongoing for over ten weeks with no end in sight, and is describedin features on pages 17 and 19. Additionally there is the usual eclectic mix of articles
from NASA and ESA which will hopefully entertain you through the dark winter nights.

F

inally, we wish every reader our very best wishes for the Festive Season and the
New Year ahead.

Contents
Zuiderzee Works
Record-breaking Year for Fire in Sakha
The Sally Ride EarthKAM
Sea Ice forming in Kuskokwim Bay
Rio de la Plata
Manually Decoding Historic Meteor M2 S-files in MeteorGIS
Looking Up - Looking Down
Shark BayAsh and Cloud Rings Over La Palma
La Palma Volcano: How Satellites help us Monitor Eruptions
Overlay Met Office Pressure Charts on Meteor M2 Images
Ice Persists in the Northwest Passage
Sahara Dust Cloud over Europe
LANDSAT: The Satellite That Might Save the Earth
NASA, USGS Release First Landsat 9 Images
Progress update: Dundee Satellite Receiving Station
The Caspian’s Shallow North
Springtime on New Zealand’s South Island
Visualising EUMETCast SAF products
Colorado River Delta
Satellite Status

NASA Earth Observatory
NASA Earth Observatory
Ed Murashie
MODIS Web Image of the Day
MODIS Web Image of the Day
Les Hamilton
Robert Moore
MODIS Web Image of the Day
NASA Earth Observatory
European Space Agency
Richard Fairman
NASA Earth Observatory
MODIS Web Image of the Day
Ed Murashie
NASA
Neil Lonie
NASA Earth Observatory
MODIS Web Image of the Day
Richard Osborne
MODIS Web Image of the Day

www.geo-web.org.uk

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Zuiderzee Works
NASA Earth Observatory
Story by Emily Cassidy

NASA image by Alan Holmes/NASA’s Ocean Color Web, using data from SeaHawk/HawkEye.

www.geo-web.org.uk

Details overleaf

4

Zuiderzee Works (continued from previous page)
Where the Netherlands meets the North Sea there is
an impressive confluence of natural and man-madefeatures. Much of the human-made infrastructureis designed to keep rising seas out of the low-lying
country. The landscape carved by nature is a hotspot
for plants and animals taking advantage of thenutrient-rich wetlands.
The Netherlands has long been shaped by floods
and by efforts to hold back the sea. A spine-likearchipelago known as the West Frisian Islands
protects the mainland of the country. Just to thesouth lies the world’s largest system of unbroken
mud flats, known as the Wadden Sea. Harbour seals,
Eurasian spoonbills and some 10,000 other speciesof flora and fauna depend on these mudflats for
migration and feeding.
The Wadden Sea used to be connected to the bay
to its south—known as the Zuiderzee—until theconstruction of the 32-kilometre Afsluitdijk in 1932.
Designed to protect the Netherlands from rising seas,
the dam also created a freshwater lake known as
Lake Ijssel.
Cutting part the Zuiderzee from the North Sea
allowed the Dutch to reclaim some of the shallow
wetlands behind the dam. The Ministry of
Infrastructure and Water Management surrounded
the wetlands east of Amsterdam with dykes anddrained them for agriculture using wind power:
land reclaimed in this manner is known as a polder.
Roughly 1,620 square kilometers of land has been

reclaimed this way. Collectively, this human-madesystem of dams, dykes, and polders is known as theZuiderzee Works.
The Wadden Sea provides a critical resting andfeeding place for millions of birds as they make theiryearly migration along the East Atlantic Flyway.
Since 2009 the area has been listed as a World
Heritage Site by the United Nations Educational,
Scientific and Cultural Organization because of its
unique ecology and importance to biodiversity.
The image above was acquired on June 1, 2021,
by the multispectral HawkEye sensor aboard the
SeaHawk CubeSat. SeaHawk is a new nanosatellite
designed to monitor phytoplankton by measuring
the colour of the ocean and coastal ecosystems.
Phytoplankton are the foundation of food webs inmarine ecosystems and they also play a large rolein the global carbon cycle by consuming about
24 percent of the carbon dioxide in the atmosphere.
Previous satellite instruments designed to measureglobal ocean colour, such as the Sea-viewing Wide
Field-of-view Sensor (SeaWiFS) had lower spatial
resolution and the large pixels made research ofmarine and coastal environments challenging.
SeaHawk was designed to fill this void by providing
data with eight times the spatial resolution of
SeaWiFS. This small satellite only recently beganroutine operations but has already proven to be a
low-cost way to measure ocean colour in coastal
ecosystems.

A Record-Breaking Year for Fire in Sakha
NASA Earth Observatory
Story by Adam Voiland

The larch forests of the Republic of Sakha (Yakutia) are like no other place on Earth.
Found in a region with some of the world’s largest seasonal temperature swings, theseboreal forests are dominated by a deciduous conifer called Larix gmelinii. This hardy
type of larch is capable of withstanding temperatures as low as -70°C and surviving infrozen permafrost soils—traits that have given the tree the most northerly range on theplanet.
In summer 2021, huge fires raged through these larch forests for months. During
Sakha’s most severe fire season in decades, more than 8.4 million hectares of forests
burned. ‘That’s an amazing amount—nearly four times the average,’ said Amber Soja, aNASA and National Institute of Aerospace associate research fellow who has conducted
field research in the region. It’s also record-breaking. More forest area burned in Sakha
than in any year since the Moderate Resolution Imaging Spectroradiometer (MODIS) on
NASA’s Terra satellite began collecting data in 2000.
In the false-colour satellite image overleaf, burned areas appear dark brown; unburned
areas are green. Patches of green within burn scars are fire refugia—areas withinfire perimeters that were unburned or only lightly burned. The Visible Infrared
Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured the image on
September 10, 2021.

Details and image overleaf

www.geo-web.org.uk

5

NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview.

For a sense of scale, Sakha is almost twice as large as Alaska, the largest U.S. state, andfive times larger than Madagascar.
‘What happens in Sakha, and in boreal forests more broadly, matters tremendously,’
said Soja. “Boreal forests store more carbon than any other type of forest in theworld—even more than tropical rainforests.”
Larix gmelinii drops its needles each winter, but the weather is so cold that there are few
decomposers (bacteria, fungi, invertebrates) around to break them down. That means
tremendous amounts of organic carbon end up accumulating in soils over time.
‘Many of the fires here burn for a long time—weeks even months. Some have burned
the same areas in multiple years,’ explained Soja. ‘These fires aren’t just spreading
across the landscape, they’re also burning downward. They’re thawing permafrost,
burning through layers of peat in some areas, and releasing stored carbon andmethane that has built up over millennia.’
Outbreaks of large fires in Sakha have happened before, including 2004, 2010, 2013,2019, and 2020. The 2019 and 2020 fire seasons were particularly extreme in Sakha’stundra regions north of the Arctic Circle. As this area baked under extreme drought andheat, it experienced the two earliest and largest fire seasons on the satellite record.
In 2021, there has not been nearly as much burning north of the Arctic Circle; instead
more of the fires occurred in forests farther south. ‘We saw a different part of Sakha
burn this year,’ Soja said. ‘But the underlying driver—droughts and heat amplified byclimate change—was the same.’www.geo-web.org.uk

6

The Sally Ride EarthKAM
Ed Murashie

Imagine being a student and being able to commanda camera onboard the International Space Station(ISS) four times a year to take a picture. That
is not a dream but the reality of the Sally Ride
EarthKAM program. If you’re a teacher or have kids
or grandkids going to school this is something you
should consider. If that is not the case, you can still
enjoy and download the images the students receive.
Best of all this is all free!
The KidSat payload was a pilot program sponsoredby NASA’s Office of Human Resources and Education.
It was announced on October 11, 1995 by NASA’s
Jet Propulsion Laboratory (JPL). KidSat principal
investigator, Dr. JoBea Way of NASA JPL, stated in
the initial press release that:‘KidSat will be designed, built and operated by
students’ and ‘the underlying philosophy of thisprogram is to stimulate young people’s interests
in learning by giving them their own piece of thespace program.’
Former astronaut Dr. Sally Ride, a professor ofphysics at University of California San Diego stated:

the shuttle’s overhead window, connected to a
Thinkpad computer which was in turn connectedto the shuttle’s communication’s system. Requests
from the schools were routed to the Thinkpad which
controlled the camera taking the images.
When the United States International Space Station
Lab Module Destiny was added in 2001, EarthKAM
was moved to that platform and has been a part ofevery ISS Expedition since Expedition 2. In 2010 thesystem was reconfigured and placed in the Window
Observational Research Facility (WORF) [4] rack in
the floor of the module. You can use Google Earth totake a tour of the ISS to see the WORF system foryourself. In the Destiny Module, the WORF systemis partially located under a black cloth used to blockstray light. Simply go to earth.google.com, click
the magnifying glass, enter ‘International Space
Station’, click on the Guided Tours tab, click on Visit
the International Space Station, and finally click on
U.S. Laboratory Module.
Sally Ride passed away in 2012 and in2013 NASA renamed the program Sally
Ride EarthKAM in her honor.

‘By attaching KidSat to the Space Shuttle,
students will be able to participate in space
exploration as astronauts and cosmonauts do’.
Ride was leading the development of the mission
operations element of KidSat with NASA’s Johnson
Space Center [1].
KidSat was truly a student-lead project with thestudents working at JPL being responsible for theflight system and computer software. Undergraduate
and high school students manned the mission
control center at the University of San Diego andwere responsible for linking the school requests
with the shuttle flight controllers. Students at
Johns Hopkins University Institute for the Academic
Advancement of Youth were responsible for theclassroom curriculum.
Three schools participated in the first KidSat mission
during shuttle mission STS-76 which launchedon March 22, 1996. The payload was again flown
in 1997 on both STS-81 and STS-86 with moreparticipating schools than before. Prior to the next
mission, the payload was renamed EarthKAM, anacronym for Earth Knowledge Acquired by Middle
school students [2]. EarthKAM flew on shuttle
missions STS-89, STS-93, and STS-99 in 1998,
1999, and 2000 respectively [3]. The hardware
consisted of a Nikon digital camera mounted in

EarthKAM image image showing New YorkThe current ISS hardware consists of a Nikon D2X
camera with either a 50 mm or 180 mm lensconnected to a laptop computer running the
EarthKAM software. The 50 mm lens provides animage 35 miles on either side of the ground track
while the 180 mm lens provides 11 miles. It is the‘ground system’, a computer and web browser,
in the classroom, that makes the program highly
educational and easy to use.
To participate a school needs only to follow thenumbered steps on the EarthKAM main webpage [3].
First, a teacher signs up once for the program andthen signs up for a mission. During a mission theywww.geo-web.org.uk

7

This is the Sally Ride EarthKAM’s ‘Select Location’ screen.

sign into the Mission Operation Center webpage and request one or more images. When the images
have been taken and uploaded to the website, the students can download and optionally annotate
them it and order prints. To learn more you can follow one of several YouTube videos [5], my recorded
presentation during the Satellite Educators Association Conference [6] or the steps outlined below.
The first step, creating an account, is nicely labeled as Step 1 on the EarthKAM home page. Click on
it and fill in the school information and how it will be used in the classroom.
If no upcoming mission has been announced, now is a great time to either explore the learning
activities by clicking on Activities in the top homepage menu bar, or to learn how the whole process
works by clicking on the Help button and then clicking on the Sally Ride EarthKAM User Guide [7]. Eachactivity, ranging from learning about orbits to how to interpret the EarthKAM images, includes ateacher guide along with a student handout. Even if you only did one activity a day there are weeks’worth of activities to keep the students busy and learning.

www.geo-web.org.uk

8EarthKAM image of Russia’s Amur river in winterWhen a mission has been announced the teacher
signs up to receive 250 codewords to be handed
out to the students. One codeword is needed foreach image requested and more codewords can berequested.
Making the Request
When the mission starts, each student participating
should fill out a Mission Targeting Sheet found on
the Help webpage for each image they would like torequest. To request an image, the student signs
into the Mission Control Center and then clicks on the
Weather tab to check out the weather in the area ofinterest. They certainly don’t want a clouded image,unless of course they are interested in taking a
picture of clouds or a hurricane. Next they clickon the Image Request tab and then select the orbitthat is closest to their target. The student needs todetermine the exact time when the ISS is closest
to their target so they can enter that time into theimage request. To do this they move the cursor
on the map to their target and see a red target on
the orbit track following close by. The red target
indicates the ISS’ best position to take an image ofthe target.
The student can either place the cursor over a cityor land feature, or they can use the plus and minus
buttons to zoom in and explore the map leaving theircursor on an interesting feature and make note of
the nearest city. The students must verify that the
distance between the chosen location and the ISS
is less than 10 miles to guarantee their location iswithin the image even if the 180 mm lens is used.
Next, they click on the Request Image button, enter oneof their codewords, the orbit number, the GMT time,
latitude and longitude from the Image Request Infobox under the map along with the city location, anda reason for this request. The city and reason help
other people looking at their image to understandwhat they found interesting about this location.
Finally they click the Submit button.
The Welcome tab webpage will display the image
requests and status. When the status changes to‘Taken’ the student can view the images on the
School Gallery webpage.

EarthKAM image taken over the Netherlands

Anyone can always click on the EarthKAM homepage
Images tab and then the Visit the Gallery [8]. From there
you can visit themed, annotated, or all the images
from specific missions. When you click on an image
you will find information about the image including
the school that took it. From there you can download
the image, view it on Google Earth, or print it out.
And did I mention—all this is free?
References
1 https://www.jpl.nasa.gov/news/students-prepare-new-kidsat-payloadto-fly-on-space-shuttle
2 https://www.nasa.gov/mission_pages/station/research/experiments/
explorer/Investigation.html?#id=87
3 https://www.earthkam.org/
4 https://www.youtube.com/watch?v=SdbFn9DOzRg
5 https://www.youtube.com/watch?v=qYXHleZBaIk
6 https://www.sated.org/conferences/conf34pics/Murashie_Presentation.
htm
7 https://www.earthkam.org/files/pdf/ISS_EarthKAM_User_Guide.pdf
8 http://images.earthkam.org/main.php

At their highest resolution, images from the
EarthKAM show great detail. As an example,
download this image of Little Italy, Melbourne,
Australia, acquired during November 2021 fromhttp://images.earthkam.org/main.php?g2_itemId=1804225

and zoom in to see the detail.

This is a small section of the ‘Little Italy’ image acquired by
EarthKAM, showing urban detail.

www.geo-web.org.uk

9

Sea Ice forming in Kuskokwim Bay
MODIS Web Image of the Day

https://modis.gsfc.nasa.gov/gallery/showall.php

Image Credit: MODIS Land Rapid Response Team, NASA GSFC

Fresh ice off the coast of southwestern Alaska shimmeredin the sunlight of an autumn day in early November 2021.
The Moderate Resolution Imaging Spectroradiometer(MODIS) on board NASA’s Aqua satellite acquired thistrue-colour image on November 11.
The icy fingers stretch across Kuskokwim Bay, a large
embayment of the Bering Sea. It receives freshwaterfrom several rivers, especially the large Kuskokwim River,a glacially turbid river that originates in the Kuskokwim
Mountains and travels approximately 900 miles throughremote territory to reach the Bay. The drainage basin thatflows into the river is the second-largest in the state of
Alaska. The river typically ices up in mid-November, whensea ice also begins to form in the Bering Sea. This year,
frigid temperatures near the ground arrived early and theannual expansion of sea ice is well underway. The rapid
river ice-up stranded a barge that was carrying building

materials down river to Eek, a town of about 400 people
in a remote area not far from the Kuskokwim River. In late
October, as the barge turned towards the Eek River, arapid drop in temperature brought a sudden freeze up of
the river, obstructing the barge’s movement. It is planned
to leave the barge in place overwinter and return torecover it in spring.
The National Weather Service reports that the sea ice
minimum for the entire Arctic occurred on September 16,
with the overall sea ice extent in Alaska farther south thanmost of the last 10 years. The transition from ice shrinking
to expansion is well underway, but the report states thatnew growth has been confined to the ice edge and islimited by sea surface temperatures. The sea surface
temperatures in the northern Bering Sea were cooler thanrecent years, spurring a less-delayed start of freeze-up in
this region.

www.geo-web.org.uk

1010

Rio de la Plata
MODIS Web Image of the Day

The Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA’s Terra satelliteacquired this true-colour image on September 16, 2021, in the waning days of winter.
Image Credit: MODIS Land Rapid Response Team, NASA GSFC

This stunning true-colour image
captures the dramatic colours
created by the mixing of muddy
river water with the clear, but saline
water of the South Atlantic Ocean.
This mixing occurs in Rio de laPlata, the muddy estuary of the
Paraná and Uruguay Rivers, whichforms part of the border between
Argentina and Uruguay. The richestuary supports both capital cities
of Buenos Aires, Argentina andMontevideo, Uruguay. These cities

appear as gray pixels on the south
shore and the north shore of Rio dela Plata. Buenos Aires is the larger
city.
The Paraná is South America’s
second longest river and drains
much of the southeastern part of thecontinent. The extensive delta of the
Paraná nearly reaches across themouth of the Uruguay River. The
rivers’ fertile soils support extensive
agriculture, including livestock, inwww.geo-web.org.uk

the region surrounding the cities.
As the rivers course through thelandscape, they accumulate large
amounts of sediment, which dumps
into the estuary along with fresh
water. The complex mixing patterncreates beautiful colours, withsediment floating near the surface
appearing in shades of tan. As
sediment sinks below the surface,
the reflectivity changes and thiscauses the colour to trend towards
green when seen from space.

11

Manually Decoding Historic Meteor M2 S-files for MeteorGIS
Les Hamilton[IN]
sat=M2source=man
mode=72k

The MeteorGIS software package authored by
Christophe Marchand has rightly become extremely
popular on account of its ability to process images
from Russia’s Meteor M2 satellite in a variety ofways, most specifically by creating geospaciallycorrected images to which overlays of coastlines,
country outlines and major cities may be added.

[OUT]
rgb=123.jpg
rgb_q=100
mono=yes
logs=noAPID70=no
VCDU=nopath=C:\Meteor\Images_M2

But MeteorGIS did not appear until late 2019, morethan five years after the Meteor M2 satellite waslaunched and commissioned. A question that has
been raised a number of times on the internet, andalso to me personally, is this: ‘Can historic Meteor
S-files dated before MeteorGIS was available, be
processed by the software’.
Although the documentation within the MeteorGIS
package suggests that this is possible, no-one to
my knowledge seems to have satisfactorily mastered
this: or if they have, they have been keeping very
quiet about it. This prompted me to carry out
some experimentation, and though the process
is somewhat contorted, it can be done! All you
require is a Meteor M2 S-file, a manual version of
LRPT Decoder and a two-line keplerian element set
for the date on which the S-file was acquired. The
various stages that have to be accomplished arelisted below.
1 Modifying the S-file
Historic S-files, created by LRPT Decoder, typicallyhave the date/time format shown below.
2020_03_22_LRPT_08-53-37.s
There is a problem here, because MeteorGIS.exe does
not recognise this format, which is characteristicof S-files created by Vasili Beriakov’s Meteor plugin
for SDRsharp. To enable data to be retrospectively
decoded by MeteorGIS, all underscores must be
replaced by hyphens, and the fragment ‘LRPT_’
deleted altogether, leaving a filename that contains
solely the date/time values, as follows.
2020-03-22-08-53-37.s[GEO]
RoughStartTimeUTC=22/03/2020
TleFileName=C:\Meteor\M2_tle.txt
Alfa_M2=110.8
Delta_M2=32.0
Alfa_M22=110.0
Delta_M22=-4.8
The recommended structure for
the M2_Man_LRPT_Decoder ini fileis shown in the grey panel above. Note that the
RoughStartTimeUTC (date) must be identical withthe date section (highlighted in red) of the S-file,although the format is different: in both cases, thedate referred to here is March 22, 2020.
Also, the satellite is specifically designated as ‘M2’
rather than ‘auto’. I find that archived S_files won’t
decode under the ‘auto’ setting in manual mode,
hence the need to be specific.
3 Keplerian Elements
Unless you have saved the then current Meteor M2
keplerian elements from the date of acquisition, youwill have to source these from the internet. The best
option is Space‑Track athttps://www.space-track.org/auth/login

If you haven’t already done so, create an account,which is a simple matter of entering a username andpassword (both of your own choices).

After editing an S-file accordingly, copy it into the
S_file folder within your MeteorGIS package.
2 The Required M2_Man_LRPT_Decoder ini file
The ini file for the manual version of LRPT Decoder
within the MeteorGIS package must contain asection headed ‘[GEO]’ so that a GCP (Ground
Control Points) file related to the S-file can becreated. The data in this file is used by MeteorGIS
to geospacially modify the decoded Meteor channel
images. The basic LRPT Decoder ini file structurewww.geo-web.org.uk

12

Once you have done so, Space‑Track opens showing
the screen at right. Click the link: Retrieve ELSET
Data by Satellite Catalog Number to advance tothe ‘Historical Elset Search’ screen. The catalogue
number for Meteor M2 is 40069, which is inserted
under ‘Entries’.
All that remains is to select the appropriate date
range for your S-file. Note that entering the samedate in the ‘From’ and ‘To‘ windows achieves nothing.
The two dates must be different to encompass
at least one complete 24-hourinterval. In the screenshot below,
selecting from June 10 to June 12
will download all relevant element
sets for Meteor M2 for bothJune 10 and June 11.
I recommend this because
sometimes keplers for the dateof the S-file don’t work. In thiseventuality, the previous day’s
keplers will usually be found to
do the trick. I don’t understand
why this should be. Perhaps there
is a conflict between Universal
Time, under which the kepler setsare listed, and Local Time which
defines the Meteor acquisition.
Once the dates are entered, clickthe ‘Load Data’ button and the
keplerian element sets will belisted at the foot of the screen.
Most days, several such sets arelisted.
In practice, it’s best to start one
day prior to the desired date andcontinue to one day afterwards.
This will download kepler sets
for both the day in question andthe previous day. The screenshot
at right shows result between
June 10 and 12, 2015, with the sets of keplerianelements listed below in the grey panel.
If you need to check which date is which, refer tothe two values underlined in red. The first two digits(15) represent the year (2015) while the last three
digits indicate the day of the year. You can determine
the date for an element set by referring to the
Day‑Of‑Year Calendar athttps://www.esrl.noaa.gov/gmd/grad/neubrew/Calendar.jsp

as illustrated for June at right. This shows thatday 161 is June 10 and Day 162 is June 11.
Now that the data are available, carefully copylines 1 and 2 of a dataset and edit them into theM2_tle.txt file. A common cause of failure is to copy
a line 2 followed by a line 1: line 1 must come firstwith line 2 below it!

www.geo-web.org.uk

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This Meteor M2 image dates from March 11, 2015, and has been retrospectively processed using MeteorGIS

4 Processing
To start processing your Meteor M2 images makesure that• the S-file has been converted to the correct format
and is placed in the S_files folder. This guarantees
that the three decoded Meteor channel images will bein the correct format to be recognised by MeteorGIS
and processed correctly.
• the M2_tle.txt file has been updated with the correct
keplerian elements• RoughStartTime in ManualLRPTDecoder.ini has
been updated with the date shown in the S-fileand you are set to go.
• Load the S-file into LRPT Decoder and watch thegreyscale images building up on screen. Most early
Meteor S-files use the 72k bit rate but if this fails try
again with 80k (some early trials used 80k). The three
Meteor channel images and stat files will be saved in
the Images_M2 folder, just as in a ‘live’ acquisition.
Note at lower left on the screen, it states ‘GEOGRID
will be calculated’.
• As soon as processing is complete, click theGenerate RGB button and the text changes to‘Calculating’ accompanied by a counter.
This is the process that creates the GCP file, but at
this point only in memory. To save the gcp file alongwith the images and stat files, you must now click
Save in the top menubar and select JPEG.
Don’t select BMP because this will not save theessential gcp file.
• The final step is to dive into the MeteorGIS
folder and double-click the default.bat file (or the
Manual_M2_GIS.bat file - they are identical) to create
the ‘Treated’ and ‘UTM’ Meteor images and save themin the FinalImages folder..
Terminology
All names used above are as found in the portable
Meteor GIS suites available from my website at
http://leshamilton.co.uk/MeteorGIS.htm

Hopefully, for users who have set up their own
MeteorGIS systems from scratch, the above
explanation is sufficiently clear for them to
implement it if so wished.

A more detailed explanation of this process is available on my website at the following URL

www.geo-web.org.uk
http://leshamilton.co.uk/ReprocessGIS.htm

14This Meteor M2 image dates from June 13, 2015, and has been retrospectively processed using MeteorGIS

Looking up - Looking down
Robert Moore
There were very distinct
cloud streets over
Lancashire at 1415 on
October 15, as seen in theimage from MSG‑4. Since
I could see these streetsfrom my window, I took aphotograph. The tiny red
marker shows my locationon the satellite image. The
photo was taken facing
to the north-east and thebuildings on the horizon are
in Bootle and Liverpool.

MSG-4 image of cloud streets above Lancashire
at 14:15 UT on October 15, 2021.

www.geo-web.org.uk

A photograph of the cloud streets taken a few
minutes after reception of the MSG-4 image.

15

Shark Bay
MODIS Web Image of the Day

Image Credit: MODIS Land Rapid Response Team, NASA GSFCLong before William Dampier—an English
explorer, pirate, and natural historian—first seteyes on the rich waters and bays he dubbed‘Shark Bay’, the wondrously biodiverse area
was well known to local indigenous peoples.
According to the Shark Bay World Heritage Site
web page, the local Malanga Aboriginal peoples
called this area Gutharraguda, a word meaning‘two waters’—and an apt description of two
protected bays formed by a pair of nearly parallelpeninsulas found off the far western Australiancoastline.
Sitting about 820 kilometres north of Perth, Shark
Bay looks a bit like the letter ‘W’ when viewed
from space. Edel Land Peninsula and Dirk Hartog
Island lie together along the western reaches, withlimestone cliffs that rise steeply along the Indian

Ocean on the peninsula and sandy dunes on
islands. Perron Peninsula sits in the center andhouses tidal flats in the west and rusty red-sanddunes in the east. Hamelin Pool is found Between
Perron Peninsula and the mainland coast.
Shark Bay has become famous for its biodiversity,
especially the massive underwater meadowsof seagrass which stretch across the eastern
shore and include 12 of the world’s 60 known
seagrass species. The Wooramel seagrass bankis the largest on Earth, spanning 1,000 square
kilometers along Shark Bay’s eastern coastline.
Probably the most unusual and fascinating formsof life here are stromatolites—layered rocks thatare created when microbes trap particles andcreate sediments. The stromatolites found here
are some of the most diverse in the world.

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16

Ash and Cloud Rings Over La Palma
NASA Earth Observatory
Story by Adam Voiland

Since the Cumbre Vieja volcano began
erupting on September 19, 2021, most of
the compelling activity has happened on the
ground. For nearly two weeks, thick sheetsof lava burned through farmland, roads andhomes on the southwestern part of La Palma,
one of the Canary Islands.
The atmospheric effects of the eruption
had been less dramatic until the CanaryIslands Volcanology Institute (INVOLCAN)
reported an increase in explosive activity
that started on October 2. In the midst of theelevated activity, the Moderate Resolution
Imaging Spectroradiometer (MODIS) on
NASA’s Terra satellite captured an image(figure 1) of a dense plume of ash streaming
south on October 4, 2021. According to
the Toulouse Volcanic Ash Advisory Center,the plume reached three kilometres on
October 4, posing a hazard to aircraft in
the area. Despite the increase in activity,
volcanologists still rank Cumbre Vieja’s
explosivity as ‘moderate’, a 2 out of 8 on the
Volcanic Explosivity Index.
The eruption has not been energetic enoughto inject large amounts of ash and gases
into the stratosphere, where they can havestrong and lasting effects on weather andclimate. However, it has been strong enoughto produce a rising column of emissions that
helped form the remarkable pattern in theclouds shown in figure 2, acquired by NASA’s
Aqua satellite on October 1, 2021.

Figure 1 - Terra MODIS image of the ash plumeThe bullseye-shaped cloud was the productof a rising column of superheated ash andgases known as the eruption column. The
buoyant column of water vapour and othergases rose rapidly upward until colliding witha drier, warmer layer of air at roughly fivekilometres altitude. The unusually warm air
above—a temperature inversion—functioned
like a lid, preventing the volcanic plume fromrising any higher. Instead, it flattened out
and spread horizontally.
Since volcanic eruptions typically havenatural ebbs and flows in their intensity,
pulses in the upward flow of the volcanic
column created concentric gravity waves
as they hit the temperature inversion andspread outward. The process is similar to
the way a stone dropped in a pond createsripples that spread outward.

Figure 2 - Aqua MODIS image of the ‘bulls eye’ shaped cloudNASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview.

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17

After Cumbre Vieja split open and began erupting on September 19, 2021, a slow-moving wall of basaltic lava began bulldozing its
way through populated parts of La Palma. Lava flows have destroyed hundreds of homes, buried dozens of kilometres of roads, andconsumed farmland as molten rock creeps down the western flank of the volcanic island toward the ocean.
NASA Earth Observatory image by Lauren Dauphin, using Landsat-8 data from the U.S. Geological Survey.

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18

La Palma Volcano: How Satellites help us Monitor Eruptions
European Space Agency

Since the Cumbre Vieja volcano began eruptingon September 19, 2021, lava has burned throughhomes, roads and farmlands causing mass
destruction on the west part of the Canary Island of
La Palma. Cumbre Vieja means ‘The Old Summit’in Spanish. Satellite imagery has helped authorities
monitor and manage the ongoing crisis. From
capturing images of the rivers of lava, to measuring
gas emissions and assessing damage, the fleet ofCopernicus Sentinel satellites has been providing
crucial data for local teams.
On October 9, it was reported that parts of thenorthern face of the volcano’s cone had collapsed,leading the lava to overflow in different directions.
On Sunday, October 11, 21 seismic movements
were detected, with the largest measuring 3.8 on the
Richter scale, according to the National Geographic
Institute of Spain (IGN).

A build-up of ash and dust on the runway forced
authorities in La Palma to close the island’s airport,
according to Spain’s airport authority AENA. It was
the second time the airport had been closed due toash build-up since the eruption began.
In stunning new images taken on October 10,
the new river of lava belching from the Cumbre
Vieja volcano was captured by the Copernicus
Sentinel-2 mission. These Sentinel-2 images havebeen processed in true colour, using the shortwave
infrared channel to highlight the new flow of lava
(figure 1).
The Volcanology Institute of the Canary Islands(Involcan) stated that the lava flow, withtemperatures up to 1240°C, destroyed the few
remaining buildings still standing north of the
Todoque neighbourhood.

Figure 1 - The New lava river as captured by Copernicus Sentinel-2
Image © contains modified Copernicus Sentinel data (2021), processed by ESA, CC BY-SA 3.0 IGO

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19

In response to the ongoing eruption, the Copernicus
Emergency Mapping Service was activated. Since
its activation, this service has released 17 mapping
products to monitor the lava flow which has affected
497 hectares of land and destroyed over 1100
buildings (as of October 8).
Satellites in orbit carry different instruments thatprovide a wealth of complementary information tobetter understand volcanic eruptions. Atmosphericsensors can identify the gases and aerosols releasedby the eruption, as well as quantify their wider
environmental impact.
This image shows the sulphur dioxide emissions
from the eruption on 6 October captured by theCopernicus Sentinel-5P satellite, moving over the
Atlantic Ocean towards Central America. Sentinel‑5P
can monitor sulphur dioxide, aerosol and ash
emitted by volcanic eruptions and follow their
movement through the atmosphere.

ESA’s Copernicus Sentinel-5P mission manager,
Claus Zehner, commented:‘This volcanic eruption demonstrates how
Sentinel data can support different operational
Copernicus services. Sentinel-5P sulphur dioxide
measurements can be used by the Copernicus
Atmospheric Monitoring Service to help aviationcompanies to avoid volcanic ash and sulphur
dioxide plume encounters.
‘Sentinel-2 lava flow measurements can support
the Copernicus Emergency Management Service incase of natural disasters like a volcanic eruption.’
Sulphur dioxide concentrations can be monitored
using the Copernicus Sentinel-5P Volcanic Sulphur
Dioxide online platform. Using data from theCopernicus Sentinel-5P satellite, the platform shows
the daily sulphur dioxide concentrations coming
primarily from volcanic sources.

Figure 2 - Sulphur dioxide concentrations on 6 October 2021
Image © contains modified Copernicus Sentinel data (2021), processed by ESA, CC BY-SA 3.0 IGO

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20

Overlay MetOffice Surface Pressure Chartsover Meteor M2 Images
Richard Fairman

Receiving and decoding weather images from NOAA andMeteor polar orbiting satellites is a real possibility withthe correct antenna, receiver/SDR dongle and software.
Currently the main live weather satellites are the USA
NOAA 15, 18, 19, and from the Russians Meteor M2.
NOAA satellites provide APT with a resolution of 4 km/
pixel but the Meteors deliver LRPT which has the higher
resolution of 1 km/pixel.
Overlaying surface pressure charts on to weather images
brings a new dimension, allowing one to visualisepressure contours and the association of cloud formations

with cold and warm fronts. Up until now the overlaying
of surface pressure charts has only been possible withexpensive proprietary software.
Now, I have developed a system to do the same using free
image manipulation software and a simple workflow taking
about ten minutes.
Prerequisites• A clear Meteor M2 Image (.PNG or .JPG file).
There is a link to the M2 image used in creating theabove composite in the Appendix.

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21• A monochrome Surface Pressure Chart that closely
matches the time and date of the M2 image. (.GIF
file). Pressure charts can be downloaded from theseweb sites as GIF files. (There is a link to the chartused in creating the above image in the Appendix).
Current charts can be downloaded from:https://www.metoffice.gov.uk/
weather/maps-and-charts/surface-pressure

Historical charts are available from:https://www.willandweather.org.uk/mycharts.php• Image manipulation software GIMP.
Download Windows or Linux versions of GIMP fromhttps://www.gimp.org/downloads/

Workflow• Save a pressure chart, as a .GIF file, close  to thedate and time or your M2 image.
• Process the pressure chart (in GIMP) to match thesize and orientation of the M2 image.
• Process the pressure chart to remove greyscale andconvert it to pure B/W.
• Make the pressure chart background transparent andcopy to clipboard.
• Resize the M2 image to match the size of thepressure chart.
• Paste the pressure chart as a layer over the M2
image.
• Manipulate the pressure layer so that features such ascountry outlines align as closely as possible.
• Adjust the opacity of the pressure layer to suit taste.
• Export  the pressure chart and M2 images as a single
file of type .PNG.
Each stage of this workflow is described in detail below.
Save a MetOffice Pressure Chart as a GIF file
Note - the Pressure Chart you save needs to be from as
close as possible to the Date and Time that your M2 image
was transmitted. Historical charts are available at:https://www.willandweather.org.uk/mycharts.php

5 Adjust the image by width to 6000 pixels.
6 Click ‘Scale’ to proceed.
Rotate the MetOffice Pressure Chart
1 Click the ‘Image’ tab and select ‘Transform/Arbitrary
Rotation’ from the drop-down menu.
2 A ‘Rotation’ dialog box will appear to enable edits.
3 Rotate the image by entering the ‘Angle’ as
37 degrees.
4 Click ‘Rotate’ to proceed.
Convert the MetOffice Pressure Chart to pure B/W
1 Click the ‘Colors’ tab and select ‘Threshold’ from thedrop-down menu.
2 A ‘Threshold’ dialog box will appear to enable edits.
3 Adjust the image by dragging the small triangle (under
the greyscale panel) left or right to achieve a pure
B/W image with minimum pixilations.
4 Click ‘OK’ to proceed.
Make the MetOffice Pressure Chart Transparent
1 Right-click over the displayed MetOffice Pressure
Chart and select ‘Colors / Color to Alpha’ from thedropdown menu.
2 A ‘Color to Alpha’ dialog box will appear with white as
the selected colour.
3 Click ‘OK’ and the GIF file will have a transparent
background indicated by a chequerboard effect.
4 Click ‘OK’ to proceed.
Copy the MetOffice Pressure Chart to the Clipboard
1 Click the ‘Edit’ tab.
2 Select ‘Copy’ from the drop-down menu.
3 The MetOffice Pressure Chart that has been scaled/rotated/pure B/W and transparent is now on the
clipboard ready for pasting atop the M2 image later.

1 Navigate to the MetOffice web site athttps://www.metoffice.gov.uk/
weather/maps-and-charts/surface-pressure

2 Click on ‘Black and White’ above the coloured chart
2 Right-click on the displayed B/W chart.
3 Select ‘Save Image as’.
4 Choose a save location and click on ‘Save’.
Scale the MetOffice Pressure Chart
1 Open GIMP.
2 Click the ‘File’ tab and import your Pressure Chart
image by selecting ‘Open… (CTRL + O)’.
3 After the image loads, click the ‘Image’ tab and select‘Scale Image’ from the drop-down menu.
4 A ‘Scale dialog’ box will appear to enable edits.

Scale the Meteor M2 image
1 Click the ‘File’ tab and import your Meteor M2 image
by selecting ‘Open… (CTRL + O)’.
2 After the image loads , click the ‘Image’ tab and select‘Scale Image’ from the drop-down menu.
3 A ‘Scale’ dialog box will appear to enable edits.
4 Adjust the image by width to 3500 pixels.
5 Click ‘Scale’ to proceed.
Paste the MetOffice Pressure Chart over the M2 image
1 Click the ‘Edit’ tab.
2 Select ‘Paste as / New layer in Place’ from the drop-downmenu.
3 Click the ‘View’ tab and select ‘Zoom‑25%’ to display theentire Meteor M2 image on screen.

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22

Note: the Met Office Pressure Chart is now overlaying
the M2 image as a separate layer but may not yet be ina position to be visible. It will have to be repositioned andaligned.
Align the MetOffice Pressure Chart over the M2 image
1 Click on the ‘Layer’ tab.
2 Select ‘Transform/ Offset’ from the drop-down menu.
3 The ‘Offset Layer’ dialog box appears.
4 It is now possible to left-click and drag the MetOffice
Pressure Chart layer so that it can be aligned withknown features, such as country outlines on theunderlying M2 image.
5 When you are happy with the alignment click ‘OK’.
Note
The angle of the M2 image varies with successive M2
passes, so you may have to adjust the rotation from the‘Layer’ tab by using ‘Transform/Abitrary Rotation’.
Adjust the Opacity of the Met Office Pressure Chart
Note: the MetOffice Pressure Chart overlaying the M2
image as a layer may obscure some of the underlying M2
image features. The opacity of the layer can be adjusted
to correct this by means of the ‘Opacity’ setting in the lower
right of the GIMP window.

This is an illustration of the Meteor M2 image used to create thelarge composite image at the top of this article.
There is a link to the full sized image below which you candownload to try out the technique in GIMP yourself.

Export the composite image as a PNG File
1 Click on the ‘File’ tab.
2 Select ‘Export’ As from the drop-down menu.
3 The ‘Export Image’ dialog box appears.
4 Rename the file with a .PNG file extension.
5 Select where you would like to save the .PNG file.
6 Click on ‘Export’.
7 The ‘Export Image’ as PNG appears.
8 Click on ‘Export’.
NoteThere is a bug in GIMP that can result in a pasted
image failing to retain its size. You can correct this byclicking the ‘Layer’ tab and selecting ‘Scale layer’ from themenu.
Appendix

This is an illustration of the Met Office Chart that was used
to create the overlay on the composite image.
There is a link below where you can download it for use in
GIMP.

The sample Meteor M2 Image shown above can be downloaded from this clickable URL

https://muglihs.sharing.bublup.com/ui/landing_page?item_id=001-i-086910fe-9df8-4b8f-942d-d576ee0832fb

The original Met Office Chart, illustrated above, can be downloaded from this clickable URL

https://muglihs.sharing.bublup.com/ui/landing_page?item_id=001-i-5ef65bc8-652a-4619-8bc3-b8677fc90b97

This composite image shown at the start of this article can be downloaded from this clickable URL
https://muglihs.sharing.bublup.com/ui/landing_page?item_id=001-i-c8e256a6-15f0-476a-97ed-53ac3fda37d8

FinallyIt’s worth mentioning that the scaling and rotation settings described in the text work well for these specific images. You
may find that you have to change these slightly for use with your own Meteor M2 images.

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23

Ice Persists in the Northwest Passage
NASA Earth Observatory
Story by Kathryn Hansen

For centuries, explorers have tested
the icy waters of the Arctic, looking
for sea routes through the cluster ofislands north of mainland Canada.
Such a route, known as the Northwest
Passage, can dramatically shorten
the journey between the Pacific andAtlantic Oceans. The decline of sea
ice in the Arctic Ocean has made thispassage increasingly viable. But as
this image shows, it’s still not always
smooth sailing.
The Moderate Resolution Imaging
Spectroradiometer (MODIS) on
NASA’s Aqua satellite acquired thisimage shown in figure 1 on August 22,
2021. It shows part of the ‘southernroute’—one of the two main routes
most feasible for the passage oflarge ships. Since about 2006, theNorthwest Passage has becomenavigable for a short period late inmost summers. As of late August thisyear, that hasn’t quite happened.
‘The southern route still has
ice,’ said Walt Meier, a sea
ice researcher at the National
Snow and Ice Data Center. ‘But
it’s possible a channel could
open up in the next couple ofweeks before freeze-up starts inearnest.’Figure 1 - Part of the southern route through the Northwest Passage
NASA Earth Observatory image by Lauren Dauphin,using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview.

In this scene, the southern routeappears mostly open except for ice
that still floats in the straits around
Victoria Island and King William
Island. Meier notes that these arecommon places for ice to collect. Sea
ice drifts south from the open Arctic
Ocean through channels on bothsides of Prince of Wales Island; it thenhits King William Island, where it pilesup.
‘It was this ice that doomed theFranklin Expedition in the 1840s,’
stated Meier. ‘They tried to go
north of King William, but the ice
closed in and crushed their ships.
Amundsen, the first to make itthrough the Northwest Passage
in 1903-1906, went south ofKing William Island, through the

Figure 2 - Both possible routes through the Northwest Passage are highlighted in red.
NASA Earth Observatory image by Lauren Dauphin,using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview.

continued on page 25

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24

continued from page 24

narrow channel between the island and the mainland.
The island protected them from the ice while they
wintered over in Gjoa Haven.’
Today, an increasing number of ships transit the passage,
including a large cruise ship that made the journey in2016. But such voyages are subject to the variableconditions from year to year.
In contrast, the U.S. Coast Guard Cutter Healy—a
combined icebreaker and science lab—is equipped tobreak through sea ice should it encounter any during its
transit through the passage this month.

The northern route is locked up with ice this year andprobably won’t clear before the seasonal re-freeze begins.
This route is less sheltered and more susceptible to the
influx of ice from the north pushing into the channels. It
has opened in the past though, notably, in 2007 and ahandful of years thereafter.
Air temperatures also play a role. Meier thinks that
average, not-too-warm temperatures in the region during
spring and summer may have been a larger factor driving
the icy conditions this year. As temperatures continue toincrease with global warming, however, the Northwest
Passage is likely to be open more often in futuresummers.

Saharan Dust Cloud over Europe
MODIS Web Image of the Day
On July 14, 2021, the Moderate Resolution Imaging
Spectroradiometer (MODIS) on board NASA’s Terrasatellite captured a true-colour image of a vast
train of dust moving from Africa into Europe. Dust
stretched from Chad and Niger (far south of thelower edge of the image) and over the Mediterranean
Sea to reach northern Poland—a distance of about
4,400 kilometres.

Tens of millions of tons of dust blow out from
northern and western Africa each year, lofted fromthe Sahara Desert by strong seasonal winds. Dust
storms can degrade air quality, but they also play
an important role in absorbing and reflecting solar
energy to regulate Earth’s climate. Dust also fertilizes
ocean and land ecosystems with iron and various
minerals that help plants and phytoplankton grow.

Image Credit: MODIS Land Rapid Response Team, NASA GSFC

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25

LANDSAT: The Satellite That Might Save the EarthPart 1 - The Program’s History
Ed Murashie
After the launch and deployment of the first Earth
Resources Technology Satellite (ERTS-1) in 1972, NASA
Administrator Dr. James C. Fletcher said “If I had to pick
one spacecraft, one Space Age development to the savethe world, I would pick ERTS and the satellites which
I believe will be evolved from it later in this decade.”
ERTS1-1 would later be renamed Landsat-1 and be thefirst of eight such satellites, including Landsat-9 launchedon September 27, 2021.
Part 1 will explain how the program got started, whichis almost as colorful as the images they capture, andcover the launch of each satellite. Part 2 will explain
each generation’s capabilities and give examples of dataapplications. Part 3 will explain where to get the nearly
50 years of free data and how to manipulate it to tell astory.
An Unexpected Announcement
To properly set the stage you need to understand what
was going on in the United States during the early 1960’s
when it came to Earth imaging. The launch of the USSR’s
first satellite Sputnik started a space race which included
the launch of the United States meteorological satellites
TIROS and Nimbus and the manned missions Mercury andGemini. TIROS-1 transmitted its first low resolution video
camera image on April 1, 1960 and the advanced 3-axis
stabilized Nimbus satellite launched on August 28, 1964.
John Glenn was the first US astronaut to both orbit the
Earth and use a handheld camera in space during his
1962 flight. He used a 35mm Ansco camera he bought at
a drug store and two that NASA supplied to take pictures
including the first landmass picture 23 minutes into his
flight. What is believed to be his very first colour imageof Earth from Space, showing north Africa, is reproduced
above. It is reputed to be John Glenn’s favourite.
NASA had been busy since 1964 working with the
Departments of the Interior and Agriculture researching
remote sensing using aircrafts including the Convair. The
Department of Defense (DOD) had its CORONA classified
reconnaissance satellite program throughout the 60’s andearly 70’s which used film return canisters.

The Ansco Autoset camera used by John Glenn toimage Earth from orbit in 1962

This color photograph of North Africa from space wastaken by John Glenn in the Friendship 7 spacecraft during
NASA’s Project Mercury MA-6 mission, Feb. 20, 1962
Credit: John Glenn Archives—The Ohio State University

Landsat’s beginnings can be traced to Dr. William
Pecora who was the director of the United States
Geological Survey (USGS), the science branch of the
Department of the Interior (DOI). Dr. Pecora, after seeing
the meteorological satellite and manned spaceflightimages, realized a satellite in orbit capable of taking
images of sufficient quality would be beneficial for Earthresource studies. He began his campaign to convince
Stewart L Udall, the secretary of the Interior, of the ideaof a satellite. Dr. Pecora asserted that the cost using asatellite would be “far less than the cost of photographing
the Earth by conventional means”. Already having explored
land resources by conventional means, the USGS enteredinto a cooperative agreement with NASA to study land andwater from space in January 1966.
On September 21, 1966 Secretary Udall announced theEarth Resources Observation Satellite (EROS) programand named Dr. Pecora as the program lead. In a separate
statement Dr. Pecora stated “we plan to fly the first satellite
in 1969” and “the cost of launching the first EROS vehicles
is not expected to exceed $20 million”.
Even though NASA was aware of and consulted on the
USGS’ interest in satellites, the casual announcement
by Secretary Udall came as surprise to most at NASA.
They felt they had to respond the same day by issuingtheir own statement which in part stated “There havebeen joint studies and discussions of possible satellite
programs but specific flight plans and patterns of funding
have yet to be worked out. Before a fully worked out
program to use operational satellites can be approved along period of experimental work must take place”. The
USGS insisted NASA should not have been surprised
since they suggested NASA include the development ofa small orbiting Earth resources observatory in their 1966
budget. Other NASA folks were interested at the prospect

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26

of developing space-based imaging technology for use on
other NASA missions.
The DOD was concerned by the announcement, theyfelt any unmanned satellite Earth resources survey
program could jeopardize their satellite reconnaissanceprogram. A publically known satellite program orbiting overhostile locations and taking images could cause hostileinternational reactions and bans. A declassified position
paper stated “It is a good time to consider the evolution of
a Presidential Policy which would direct NASA toward an
Earth resources survey program, aircraft oriented, which
would be more economical and productive than present
ERS program proposals and would not conflict with the
National Intelligence Satellite Collection Programs.”
Under New Management
The February 17, 1967 edition of the Missile/Space
Daily announced that “the Department of Interior has
relinquished management of its EROS program to NASA”
and that “there has been a little friction over the program
between people at NASA and the EROS officials at
the U.S. Geological Survey - largely, it seems, over thetiming of the project”. The USGS still wanted to launch
the first operational satellite in 1969. Insisting there wereflight ready systems, they issued their performance
specifications to NASA on October 21, 1966. NASAinsisted the first missions were research rated and that
more research had to go into the sensors and data
communications. They issued a statement saying “It isclear that many aspects of the spacecraft dictated byyour performance specifications are just at or beyond thecurrent state of the art”. NASA pushed forward on theirschedule with Goddard Space Flight Center by issuing
proposal requests for mission analyses and spacecraft
designs. One of the proposals came from TRW Systems
Group with its extensive 18 volumes based on the Orbiting
Geophysical Observatory satellite only to be shelved infavor of using the Nimbus satellite platform.
1969 was a busy year for the ERTS research and budget
approval. The Apollo 9 crew was not only checking out
the lunar lander for the first time in Earth orbit, but theyalso ran multispectral terrain photography experimentS065. The experiment consisted of four Hasselblad 70
mm cameras mounted to the command module’s hatch
window. False color infrared, green filtered, red filtered,and black and white infrared images were taken in aneffort to find the best types of images to use to study the
Earth. Meanwhile the public was checking out the Nimbus
III model and Earth Resources Technology Satellite
concept model at Disneyland featured in the “Benefits
from Space” exhibit at the Carousel of Progress. The year
ended with the Senate approving NASA’s Earth resources
survey program budget of 25.1 million split two ways: 11
million for its aircraft program and 14.1 million for two
ERTS satellites.
Between the end of 1969 and the middle of 1970 NASA
had a contract with its key suppliers. General Electric, thefolks that manufactured the Nimbus, would be the prime
contractor and supply the spacecraft, data collection, andhandling systems. Radio Corporation of America (RCA),
who designed TIROS and its cameras, would supply thethree return beam Videocon (RBV) cameras and video
tape recorder. Hughes Aircraft Company would supply themultispectral scanner (MSS).
“Mother of Landsat”
Some people arguably call Dr. William Pecora “the father
of Landsat” but without question Virginia T Norwood is “themother of Landsat”. Virginia was a Landsat Instrument
Engineer at Hughes
Aircraft Company who led
the imager team to design
the multispectral scanner.
She is a remarkable andinspiring woman whosestory is worth reading
about. Her list of otheraccomplishments includes
a mathematics degreefrom Massachusetts
Institute of Technology,
a patent at age 22 for aweather balloon radarreflector while working at
Virginia Norwood
US Army Signal Corps
Photo credit: Gail Ginder
Laboratories, designed
the Surveyor’s moon lander transmitter, helped design
many other antennas, and headed up the Hughes Aircraft
Company Microwave Division. This year at age 94 she
was awarded the Lifetime Achievement Award fromthe American Society for Photogrammetry and Remote
Sensing and attended the Landsat‑9 launch.
To learn more about this highly talented lady, visit the two
URLs below:
https://landsat.gsfc.nasa.gov/article/
virginia-t-norwood-mother-landsat
https://www.technologyreview.com/2021/06/29/1025732/
the-woman-who-brought-us-the-world/

Mass Storage
While NASA and its subcontractors were busy with the
hardware designs, the DOI and USGS were busy planningand implementing the EROS Data Center. The data center
originally was the data storage, retrieval, reproduction,and dissemination center for ERTS imagery, USGS
aerial photography, and NASA aircraft data for the public.
Today it is that and more after expanding in 1996. It is aground station for receiving the telemetry and image datafrom Landsats and other satellites, receives data frominternational ground stations, and is an Earth resources
research location. The initial study by RCA showed thata small location “in the Midwest” between Fargo, North
Dakota and Topeka, Kansas was the best location forreception of ERTS over the continental United States. After
lobbying by South Dakota Senator Karl Mundt, President
Richard Nixon wrote in a letter dated April 2, 1970, “I shareyour pleasure that it was possible to designate Sioux
Falls as the site for the Data Receiving Center as part of
the ERTS-EROS program”. Ground breaking on the $5
million 120,000 square foot facility took place on April 13,

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27

1972 and its dedication was on August 7, 1973. During theconstruction, GSFC would process the ERTS data until the
EROS Data Center was ready. Today the data center holds
an estimate of 65 petabytes of data going back to the
1930s and employs over 600 people.
ERTS-A Launch
One program milestone occurred during
September 22-24, 1970 when GE held the ERTS
conceptual design review. Another occurred in March
1971 when NASA locked-in the ERTS designs and final
construction was allowed to continue. A major milestone
occurred on Sunday July 23, 1972 when ERTS-A
successfully launched from Vandenberg Air Force Base(VAFB) in California, but it was not without suspense.
This is the very first MSS image received from Landsat‑1,
showing a region around the city of Dallas, Texas.
Image: NASAAt an ERTS-B prelaunch press briefing on
January 14, 1975, NASA Associate Administrator Charles
Mathews announced that once in orbit ERTS-B would
be renamed Landsat-2 and ERTS-1 would be renamed
Landsat-1. NASA thought the name Landsat would
complement the name of a planned ocean observing
program named Seasat. ERTS-B successfully launched
on January 22, 1975 from VAFB, the same location all
Landsat launches have occurred, on board an improved
two-stage Delta rocket. Operations ceased in 1982 due toa malfunctioning attitude control system and ERTS-B, now
Landsat-2, was finally decommissioned on July 27, 1983.

ESTS-1 / Landsat-1
Photo NASA / USGS

A launch delay called on Thursday July 20th moved thelaunch to Saturday July 22nd due to a concern regarding
the fairing jettison. Another launch delay moved the launchto Sunday July 23rd at 10:54 AM due to an erroneous faulty
indicator on an auxiliary engine. But finally at 11:06 AM
PDT ERTS-A launched on board a two-stage Thor-Deltarocket and became ERTS-1 once in orbit. The first MSS
images were received the next day and the first in theLandsat archive received on July 25, 1972 were of Dallas,
Texas area.
Landsat-2 through Landsat-5
The 1970 NASA budget called for two similar ERTS
satellites, ERTS-A and ERTS-B. Each was designed tohave a one year operational life span and ERTS-B was
to launch approximately 15 months after ERTS-A. Even
though the RBV imager only operated from July 23, 1972
until August 5, 1972, the rest of ERTS-1 continued tooperate well past its one year designed lifetime. It was
finally decommissioned on January 6, 1978. ERTS-1’slongevity was fortunate because ERTS-B’s launch wasdelayed for a year while NASA studied ERTS-1’s results. A
Senate committee was not happy with the delay and called
NASA to explain it in October 1974.

ESTS-1 / Landsat-1 pictured on its launchpad
Photo: NASA

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28

Defining and budgeting ERTS-C was a struggle between
NASA and the Office of Management and Budget (OMB).
NASA believed that an ERTS-C research satellite was
required because it would be “technically more advanced
than ERTS-1 and -B, will be required to demonstrate
fully future operational potentials ...” They also believed itneeded to be budgeted for 1976 because “a gap between
ERTS-B and -C would ‘dead-end’ critical experiments;
would tend to dissipate the technical teams”. The Officeof Management and Budget believed “that continuity ofdata is not necessary to carry out an effective assessmentof ERTS technology” and that “consideration of ERTS-C
should be deferred to next year’s budget (1977) whenmore information will be available to the Administration”.
The final decision was that NASA would absorb the cost of
ERTS-C in its 1976 budget and would require $40 million
additional in FY 1977 and FY 1978. ERTS-C would also
be the last research satellite before going operational.
Negotiations delayed the construction and launch of
ERTS-C until March 5, 1978. Once in orbit ERTS-C was
renamed Landsat-3. ERTS-C was similar in design to
ERTS-A and B and operated until March 31, 1983.
Landsat-D and Landsat-D Prime both used the same
spacecraft bus which differed from the one used for
ERTS‑1, -2, and -3 and were designed with a three year
lifetime. They were built by GE Astro Space and used
Fairchild’s Multi-mission Modular Spacecraft (MMS) with aLandsat Instrument Module (IM). The RBV video cameras
were replaced with a Thematic Mapper (TM) and were
the first NASA satellites to use the Global Positioning
System (GPS). Landsat-D successfully launched on July16, 1982 and was renamed Landsat-4. It was plagued withantenna and solar panel problems but managed to operateintermittently until December 14, 1993 when it could nolonger transmit data. All previous Landsats were operatedby NASA but on January 31, 1983 Landsat-D satellite
operations were transferred to the National Oceanic andAtmospheric Administration (NOAA). NOAA had been
operating the weather satellites but this would be the firsttime they also operated Landsat.

Due to the Landsat-D issues, modifications were madeto Landsat-D Prime and it was launched earlier than
expected on March 1, 1984, and renamed Landsat-5
once in orbit. It had its own problems but still managed
to operate until January 6, 2013, which was long enoughfor it to set a new Guinness World Record for “Longestoperating Earth observation satellite” at 28 years and
10 months.
Commercialization
The Land Remote-Sensing Commercialization Act of1984 was enacted on July 17, 1984 after the launch ofLandsat-5. One of the findings was “competitive, marketdriven private sector involvement in land remote sensing
is in the national interest of the United States.” Anotherkey finding was “such cooperation should be structured to
involve the minimum practicable amount of support andregulation by Federal Government”. One of the outcomesof the act was the Hughes Aircraft Company and RCA
partnering in 1985 to form the Earth Observation Satellite
Company (EOSAT) who had a ten-year contract to
exclusivity rights to market Landsat data and were tasked
with building Landsat-6 and -7. Even by 1989 EOSAT
was still having problems making a profit and NOAA, who
was supplying financial backing, announced they would
shut Landsat-4 and -5 due to a lack of money. Congress
stepped in and provided emergency funding, which they
continue to do every year to the tune of $500 million. The
once promised customer cost of $2 per Landsat image
was now running $4000 and the number of customers was
dwindling.
Congress realized the valuable national asset that Landsat
represented, so on October 28, 1992 the Land Remote
Sensing Policy Act of 1992 was passed which repealed the1984 Act. The following key findings can be found in theact: “Recognizing the importance of the Landsat programin helping to meet national and commercial objectives,
the President approved ... a National Space Policy
Directive which ... commits the United States to ensuring
the continuity of Landsat coverage into the 21st century.
Unenhanced Landsat‑7 data should be made available
to all users at the cost of fulfilling user requests. Landsat
remains an unclassified program that operates according
to the principles of open skies and nondiscriminatory
access. Development of the remote sensing market
and the provision of commercial value-added services
based on remote sensing data should remain exclusively

Landsat-5
Image: USGS

A visualisation of Landsat-9 in orbit
Image: NASA

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29

Landsat Timeline

the function of the private sector.” The last finding
allows companies like Google to use Landsat andother sources of satellite images, like those from
Copernicus, in their Google Earth program. EOSAT
ceased business at the end of 1992 and now Landsat
had the financial backing of the U.S. Government.
Landsat-6 could be launched and Landsat-7 could bebuilt.
Landsat-6 through Landsat-9
The Landsat-6 was manufactured by GE AstroSpace and the spacecraft bus was based on RCA’s
Advanced TIROS-N spacecraft design which waswhich was used in the NOAA and DMSP weather
satellites. It is worth noting on your scorecard that
GE acquired RCA in 1986 to form the GE AstroSpace Division.
The entire division was sold to Martin Marietta
in 1993 which merged with Lockheed in 1995
to form the Lockheed Martin we know today.
Landsat was launched on October 5, 1993 on a
Titan II rocket used for the first and last time in theLandsat program. It failed to achieve orbit when thehydrazine manifold ruptured and the spacecraft, after
separating from the booster, was not able to achieve
orbit and fell back into the Indian Ocean.
Landsat-7 was similar to Landsat-6 and successfullylaunched on April 15, 1999 on a Delta II rocket. It
carried on the Enhanced Thematic Mapper Plus
(ETM+) which was an improvement of the ETM
carried on the Landsat-6. The Scan Line Corrector(SLC) failed on May 31, 2003, which causes gaps inwhat is called Landsat 7 ETM+ SLC-off data images.
Landsat-7 is still considered operational but will be

removed from service when Landsat-9 becomes
operational, well past its five-year design life.
Landsat Data Continuity Mission (LDCM) spacecraft
was built by Orbital Sciences Corporation using
its LEOStar-3 satellite bus and also has a design
life of five years. The spacecraft has two newsensors, the Operational Land Imager (OLI) and the
Thermal InfraRed Sensor (TIRS). LDCM launchedon February 11, 2013 on board an Atlas V rocket
and renamed Landsat-8 once in orbit. It is still
operational.
Landsat-9 is similar to Landsat-8 except it has
improved versions of the OLI and TIRS, the OLI-2
and TIRS-2. The satellite was designed and built by
Northrop Grumman Space Systems who acquired
Orbital ATK in 2018. Orbital ATK was a merger
between Orbital Sciences Corporation and Alliant
Techsystems in 2014. Landsat-9 launched on
September 27, 2021 and is currently going througha 100-day check out before going operational andbeing handed over to the USGS. The first image wasreceived on October 31, 2021.
More information about the Landsat missions can befound at the following URL
https://www.usgs.gov/
core-science-systems/nli/landsat

Next TimePart 2 will examine the Landsat imagers across thegenerations which could be helpful if you want touse generational Landsat data. Also covered will beapplication examples which might help to explain why
Landsat might be the satellite that will save the Earth.

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30

NASA, USGS Release First Landsat-9 Images
NASA

Mangroves are prominent along the northwest coast of Australia. The first image collected by Landsat 9, on October. 31, 2021, showsmangroves clustered in protected inlets and bays on the edge of the Indian Ocean. Fluffy cumulus clouds and high-altitude cirrus
clouds hover nearby. The aqua colours of the shallow near-shore waters give way to the deep, dark blues of the ocean.
Credit: NASA

Landsat 9, a joint mission between NASA and the U.S.
Geological Survey (USGS) that launched Sept. 27, 2021,
has collected its first light images of Earth. The images, allacquired Oct. 31, are available online athttps://www.nasa.gov/content/landsat-9-image-gallery.These images provide a preview of how the mission
will help people manage vital natural resources andunderstand the impacts of climate change, adding toLandsat’s unparalleled data record that spans nearly 50
years of space-based Earth observation.

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31

Progress update forthe Dundee Satellite Station (DSS) Ltd Ground Station
November 2021
Neil Lonie
Readers of earlier articles will beaware that this initiative follows
the closure of the University of
Dundee Satellite Receiving Stationand our rescuing of the antennas
and related equipment which were
due to be disposed of. Dundee
Satellite Station (DSS) Ltd wasformed in order to relocate thestation to a new site and operate
as a commercial entity.
Since our last update in
September 2020, significant
progress has been made inestablishing the new groundstation at the former RAF Errol
Airfield, west of Dundee. Our first
two tracking antennas were fully
serviced, installed and tested by
the end of 2020. One of thesehas been used for routine AVHRR
sensor data reception from NOAA
and MetOp (L-band) satellites withthe most recent images of the UK
posted on our website and freely
available (Figure 1).
The other antenna was upgradedto a dual X & S band system forsatellite Telemetry, Tracking andCommand (TT&C) operations ofsmall satellites. It has been used
to provide commercial services
since early 2021, generating
essential revenue to operate thestation and move forward withfurther developments.
Over the course of 2021 the site
has more than doubled in area toaccommodate additional antennas.
Another pair of concrete andstructural steel beam bases wereconstructed, one of which has
increased size and mass to allow
an antenna of up to five metresdiameter should the need arise
in future. Our next two tracking
antennas have been completely
refurbished, serviced andmounted on their new bases withassociated cable runs, control andFigure 1 - An example satellite image from the website - AVHRR false-colour image fromNOAA-18 on November 24, 2021 at 1120 UTC. See up to date images at:https://www.dundeesat.co.uk/

receiver equipment etc. installed.
The first of these antennas has
been on test for the past few
weeks, routinely acquiring MODIS
and VIIRS sensor data fromNASA EOS and NPOESS (X-band)satellites.
We anticipate the other antenna
being ready for initial testing
within the next month but now
have all four tracking antennas
installed, in-line with our original
local authority planning approval(Figure 2). Longer term, theconfiguration and capability ofeach antenna will depend on
future customer requirements
for small satellite support,
but the intention is to retain

www.geo-web.org.uk

remote sensing data reception
capability for X and L-band polar
orbiting satellites and ideally add
capability to receive geostationary
satellite data.
In order to support more small
satellite customers, provide users
with EO data as part of regular
operations and pursue researchcollaborations, additional site
development work and fundingis needed. Key to all of these isprovision of direct fibre internet
connectivity to the site. Currently
we use a wireless connection
giving 100 Mb/s upload anddownload capacity. This was the
only option for initial operations
and has been adequate so far, but

32

Figure 2 - The current situation with construction of the ground station, showing all four of the planned tracking
antennas now in place. Left to right are the 2.8 m, 2.4 m, 3.7 m and second 2.8 m antennas.

Figure - 3 Civil works to install our fibre cable duct and boxes along a 500 m route around the airfield.

the increased capacity of direct
fibre was always essential toexpand activities. The process hastaken much longer than hopedfor various reasons, not least theapproximate 500 metre distanceto the nearest fibre infrastructure,
identifying a suitable connection
route with wayleave agreement,
and the associated installation
costs.
Major inroads on this issue havebeen made in recent weeks.
They include securing Michelin
Development business support
to assist with installation costs,

enabling us to place an official
order through our ISP andconfirm the connection routeand wayleave. The civil works toinstall a fibre cable duct acrossthe airfield to the public routeare currently ongoing (Figure 3)
and we now anticipate our fibre
connection will be installed and'live' by the end of 2021.
In terms of EO data service
provision, there are other aspects
to address such as establishingdata processing and archiving
facilities, plus a website thatallows user access to resulting

products. We will investigate
options to support this in-house,or possibly through partner
agreements. However, as soon as
our fibre connectivity is 'live' wewill have the data distribution
capacity to support users that
require access to our 'raw' EO
data in near real-time and who
have their own data processing
facilities.
On behalf of DSS Ltd I would
like to express our thanks again
to the members of GEO for theircontinued support and interest in
the new ground station.

Any reader minded to support the Dundee Satelllite Station can do so through their GoFundMe page (Ed.)
https://www.gofundme.com/f/dundee-satellite-receiving-station
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33

The Caspian’s Shallow North
NASA Earth Observatory
Story by Adam Voiland

NASA Earth Observatory image by Lauren Dauphin,using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. .

In many parts of the world, sea levels are rising due
to global warming. But scientists note that warming
and increased evaporation are likely to play out
differently for inland seas and lakes.
In the case of the Caspian Sea (technically a lake),scientists anticipate rapid declines in water levels in
the coming decades and centuries. Radar altimetry
data collected by multiple satellites and compiled
by NASA’s Global Water Monitor indicate that the
Caspian’s water levels have already been dropping
since the mid-1990s.
By one estimate, Caspian water levels could dropby as much as 18 metres by the end of the 21st
century, enough that it would lose about a quarterof its area and uncover about 93,000 square
kilometres of dry land. That’s an area about as large
as Portugal.
Much of this new land would come from thenorthern Caspian, a shallow zone that holds justone percent of the lake’s volume and has an average
depth of between 5 and 6 metres. For comparison,
the deepest parts of the lake stretch down morethan 1,000 metres below sea level. The Moderate
Resolution Imaging Spectroradiometer (MODIS) on
NASA’s Aqua satellite acquired this natural-colour
image of the northern Caspian on July 17, 2021.
Suspended sediment delivered by the inflowing
Volga and Ural rivers had discoloured the waters in
the northern part of the lake, while winds may also
have stirred up sediment.
Losing the northern part of the Caspian could have
major ecological consequences. Its shallow waters
teem with molluscs, crustaceans, fish, and birds,
and seals raise their pups on winter ice that usually
only forms in this part of the lake.
“Current protected areas in the CaspianSea, most of which cover coastal ecosystems
including highly coveted wetlands such as theVolga Delta and other Ramsar sites (wetlandsof international importance named after the
Caspian coastal city of Ramsar, Iran) will betransformed beyond recognition,”
wrote a group of European scientists in
Communications Earth & Environment.

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34

ESA’s Copernicus Sentinel-2 mission captured this magnificent image of the cloud free Shetland Islands
on July 1, 2021 with a turquoise-coloured bloom visible to their east. This is assumed to be a bloom of
coccolithophores – a type of microscopic marine alga that inhabits the upper layer of the sea.
Image contains
modified Copernicus Sentinel data (2021),
www.geo-web.org.uk
processed by ESA, CC BY-SA 3.0 IGO

35
35

Springtime on New Zealand’s South Island
MODIS Web Image of the Day

Credit: MODIS Land Rapid Response Team, NASA GSFC

Snow caps the spine of New Zealand’s Southern Alps as
sun shines on the springtime flush of green vegetationin late October 2021. The Moderate Resolution Imaging
Spectroradiometer (MODIS) on board NASA’s Terrasatellite acquired this true-colour image on October 22.
The intense colours—ranging from deep brown to brightgreen to stark white—give New Zealand’s South Island
its intense beauty. The tall peaks of the Southern Alps
retain snow year-round and divide the country into theextremely moist western shores and the dryer land east of

the mountains. The highest peak in New Zealand is Aoraki/
Mount Cook, which rises to 3,754 metres.
Bright colours tint the waters of the Tasman Sea off thewestern coast. These jewel-tones are the result of a bloomof small plant-like organisms known as phytoplankton.
Present in these waters year-round in small numbers,
when temperature, hours of sunshine and nutrient
availability are just right, the organisms reproduce
explosively creating huge blooms that can easily be seenfrom space.

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36

Colorado River Delta
MODIS Web Image of the Day

Image Credit: MODIS Land Rapid Response Team, NASA GSFC.

The grand Colorado River once flowed freely from its
source in the central Rocky Mountains in Colorado
through about 2,330 kilometres of arid, spectacular
scenery across five states before spilling into the northern
Gulf of California. Over time, however, the river’s water
has proven so essential to human life and livelihoods
that it has been siphoned off for crop irrigation and forresidential use. Only about 10% of all water that flows
into the Colorado River actually makes it into Mexico.
Once in Mexico, most of those remnants are also used for
agriculture or drinking water.
The harnessing of the Colorado transformed the Colorado
River Delta. Once filled with lush marshland and many
braided channels, the Delta now has diminished into sandy
mud flats and scattered areas of marshland. The former
rich wetland and riparian ecosystem contrasted strongly
against the arid desert and served as an oasis, supporting
cottonwood and willow and creating breeding grounds
for a large number of native species. With the loss of theColorado’s water, invasive species moved in while thepopulation of native ones dropped steeply.
A joint effort between Mexico and the United Statesbrings some hope to save some of the remaining criticalecosystems once found so richly throughout the Colorado
River Delta. The Colorado River Binational Agreement
permitted a pulse flow of water from Morelos Dam in 2014
that brought water once again to the Delta. Even this brief
flow helped encourage growth of trees and increased
nesting bird populations. The current agreement broughta flow of water measuring 35,000 acre-feet (11.4 billion
gallons) through the river to reach the Delta between
May 1 and October 11, 2021. This annual life-enhancing
baptism, which will occur until 2026, is expected tohelp restore parts of the Delta and support habitat for
threatened species.
On November 4, 2021, the Moderate Resolution Imaging
Spectroradiometer (MODIS) on board NASA’s Aqua
satellite acquired this true-colour image of the Colorado
River Delta from the Salton Sea to the Gulf of California.
Patchworks of green appear at every location where waterflows through the river or where water can be diverted
to support agriculture. The orange-tinted sands of theSonoran Desert can be seen in the east while bright whitesalt flats sit on the western banks of the Delta. A few areasof dark blue along the Delta are most likely pools createdby the flow emitted during the summer and early fall of thisyear.

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37

Visualising EUMETCast SAF products
Richard Osborne

One feature of the EUMETCast product stream that
doesn’t seem to attract much attention from the amateur
user group is the output from the Satellite Application
Facilities (SAF) network. EUMETSAT supports eight
different SAF centres, each concentrating on a different
aspect of meteorological data that are derived fromGeostationary and Low Earth Orbiting (LEO) satellites.
Selected data from seven of them is available on
EUMETCast.
As an experiment, I decided that I would try and visualise
as many of the SAF products as possible on a Windows
based system, so I embarked on a personal research anddevelopment programme. Of course, images derived fromthe SAF products are freely available on the internet but
this is not the point. I wanted to do this as an exercise in‘self-training’ and to better understand the products.
I need to state that I am not a software or meteorologicalexpert, and that the article should not be interpreted as an
authoritative tutorial or ‘how to’ guide. It merely describes
my own efforts, interpretations and understanding (possibly
incorrect and misguided) in the hope that some readers
may find the material of interest.
First Steps
I started by exploring the websites of the individual SAF
providers, looking for documentation and recommendations(if any) for software applications that could be used tovisualise their products. I discovered that the training
websites provided by EUMETSAT and EUMeTrain were aparticularly rich source of relevant information. After a shorttime, it became clear that each SAF provider had their own
particular method of encapsulating data for transmission
over the EUMETCast network, and there would be no‘one size fits all’ solution for visualising the data. Each one
would need a different approach.
EUMETCast carries data from seven SAF providers. Aftera quick analysis, I decided not to pursue the Climate
Monitoring SAF as it only provided a very small amountof data over EUMETCast: nor the Radio Occultation
Meteorology, as this did not provide Earth referenced
images as such. I then examined the remaining five inmore detail and the general characteristics are given in
Table 1.
SAF Provider

As far as I am aware, every product available from the
SAF providers listed in Table 1 can be viewed as a twodimensional image which contains a representation of a
specific property such as temperature, wind, ice etc. In
addition, the location of the image with reference to theearth is also available which allows for the addition of abasemap to provide coastlines and other geo-referenced
features.
I established that four different data formats are used
across the SAF providers with the predominant data format
being netCDF. This also appears to be the format of choicefor new and future products. Indeed, GOES ABI images
are already supplied in netCDF format as will those ofMeteosat Third Generation.
All these formats have the property of being “selfdescribing” in common. In simple terms, the data is split
into two parts - the operational data itself and metadata
which describes how the operational data is organisedand can be interpreted. Within the rules of each format, aprovider can structure the data in whatever manner theyplease, making the decoding and visualisation of the dataa potentially difficult task. In addition, BUFR and GRIB
formats are table driven and rely on the local availabilityof relevant tables that are generated by the World
Meteorological Organisation.
Software Applications
Note: My observations and descriptions of the various
software applications relate solely to their use with SAF
products provided by the EUMETCast network. The
majority of these applications can also be used with otherdata sources and compatible EUMETCast products.
My next task was to seek out candidate software
applications for visualising the data formats described inTable 1. As a non-programmer, I looked for easy solutions
based on ‘point and click’ applications first, startingwith SatSignal products which I knew and following onwith suggestions from the SAF providers themselves.
I then searched further afield within the meteorologicalcommunity, looking for potential software solutions with arelevance to the SAF products.

Abbreviation Theme

Data Format(s)Ocean & Sea Ice

OSI

Ocean temperatures, sea ice, global
windsLand Surface
Analysis

LSA

Solar Radiation effects, vegetation,
Evapotranspiration, wildfires

Hydrology

H SAF

Precipitation, soil moisture, snow

BUFR, GRIB, HDF5, netCDF

Nowcasting

NWC

Cloud properties

netCDF

AtmosphericCompositionAC

Atmospheric Trace gases

HDF5, BUFR

netCDF
HDF5

Table 1: General SAF Characteristics

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38

My searches revealed a number of possibilities and asummary of my findings is shown in Table 2 below. The
Category heading is my own derivation which I shalldescribe in more detail shortly. In general, the most‘user friendly’ applications are at the top of the table andthe most powerful at the bottom.
Please note that the intention of this article is to commenton the suitability of each application for visualising the
SAF products and I will not be providing instruction for
their use. However, I will identify particular obstacles that I
encountered.
EUMETCast Ready
This category is so named because I understand thatthese applications were intended to handle EUMETCast
data ‘out of the box’: in other words, once installed, a few
mouse clicks were all that were required to provide usable
images. I had used these applications in the past so I
was already aware of their general capabilities but had
not evaluated them over the full range of SAF products.
Significantly, none of the applications in this category could
handle the netCDF data format, so it was clear that othersolutions were needed for this.
BUFRdisplay(www.elnath.org.uk)
For visualising BUFR products, Francis Breame’s excellent
BUFRdisplay is the “goto” application. It worked for all the
SAF products that I tried. There is always the danger that
BUFRdisplay does not have the relevant tables installed
but I didn’t encounter this potential problem. Coastlines/
country boundaries are displayed and it can open
compressed files.
GRIB Viewer(http://www.satsignal.eu/software/grib-viewer.htm)
The GRIB Viewer from David Taylor worked well for the
SAF products that I tried except one. Once I had tried
using generic tools tools to visualise the GRIB data, I
appreciated that the GRIB Viewer did a lot of work in the
background to provide an image that was easy to interpretand also easy to save in a 3712 x 3712 pixel format thatmatched the MSG optical image resolution. Coastlines/
country boundaries are displayed and it can open
compressed files.

Category
EUMETCast Ready
Generic

Scientific Analysis andPresentation
Geographic Information
Systems (GIS)
General Purpose
Software

HDF Viewer(http://www.satsignal.eu/software/hdf-viewer.htm)
Although the title of the application suggests that it is a
generic HDF viewer, it only worked with the LSA SAF.
Even then, it would only visualise a subset of the LSA SAF
product range. I believe that the reason for this is historicaland I will expand on this in a following section coveringthe LSA SAF. Coastlines/country boundaries are displayed
although I found some products (e.g. albedo) where they
were not properly aligned for some reason. It can open
compressed files.
Generic
My generic category covers freely available software
applications (viewers) that are capable of visualisingat least one of the SAF data formats and can handle arange of products that is not restricted to EUMETCast.
As a result, the viewers allow for a considerable degreeof customisation which requires effort from the user
to produce an image that brings out wanted features.
Although this article is about usage of these viewers on a
Windows system, they all work equally well (if not faster)under Linux because they are all Java based.
To produce a two dimensional image from a SAF productfile, the generic viewers need to be provided withobservational data that has a two dimensional structure
where the location of each and every pixel on a flat canvas
is represented by an X and Y co-ordinate. In addition, theviewers need to recognise this data structure otherwise
they will not attempt to build the image.
If the X and Y co-ordinates include longitude andlatitude, the image can be located on, and combined
with, a basemap containing coastlines and other optionalfeatures—assuming that the application has this capability.
This representation constitutes a Geographic Co-ordinate
System and it tells the application where each pixel islocated on the basemap. An alternative method of locatingeach pixel is called a Projection Co-ordinate System whichtells the application how to calculate the position of eachpixel based on a definition of the projection to use and aset of values for use in the calculation.
In the following sub-sections, I will describe my experience
with each of the generic viewers.

Software Application NameBUFRdisplay
GRIB Viewer
HDF Viewer
Panoply
McIDAS-V
Weather and Climate Toolkit (WCT)ESA SNAPHDFView
MATLAB
R
Generic Mapping Tools (GMT)QGISILWIS386 + GEONETCast toolbox

Data Format Capability
BUFR
GRIB
HDF5
netCDF, HDF, GRIB
netCDF, GRIB
netCDF, HDF, GRIB
netCDF, HDF
HDF5, netCDF
netCDF, HDF, GRIB
netCDF, HDF, GRIB
netCDF
netCDF, HDF
netCDF, HDF, GRIB, BUFR?

Python, C (examples)

netCDF, HDF, GRIB, BUFR

Table 2: Candidate Software for Visualising SAF Products

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Panoply(https://www.giss.nasa.gov/tools/panoply)
Panoply is provided by NASA and is the most cited
viewer as mentioned by the various SAF websites andtraining modules, and is also my own viewer of choice.
I have found it to be the most robust in the sense thatit can successfully open and provide basic information
including metadata for almost all the SAF files, even if it
is unable to form an image. It can also work directly withthe compressed files provided by EUMETCast without theneed for prior decompression.
When Panoply opens a file, it analyses the dimensional
structure of all the variables and provides a data tree
where each variable has dimensional property allocated toit. For plottable variables, this can be one of three types.
• Geo2D - The variable has full geo-location informationand can be displayed on a basemap.
• 2D - The variable does not have recognisable geolocation information but can be displayed as a twodimensional image.
• 1D - The variable can only be displayed as a graph(line plot)
The downsides with Panoply, from my perspective, are thelack of documentation and also the lack of a command line
interface or scripting functions. However, it does allow one
set of preferences to be stored, such as map projection
and colour table, and these are implemented when theapplication starts. I discovered that the preferences areheld in an XML file so it may be possible to prepare
multiple versions of this file and swap them in and out asrequired but I have not tried this approach to date.
McIDAS-V(https://www.ssec.wisc.edu/mcidas/software/v/)
McIDAS-V is a comprehensive viewer for satellite imagery
and derived products and is provided by the University of
Wisconsin-Madison. It can also analyse and manipulate
data with mathematical functions although I have not used
this capability. It cannot open compressed files.
It has comprehensive documentation, a command line
interface and a scripting capability using Jython (this is
the same as Python but running on a Java engine). It canalso display images on a three dimensional globe thatcan be rotated under user control. However, I did not findthe interface to be intuitive, partly because of the large
range of functions available. One feature that appears to
be unique to McIDAS-V is the ability to view multiple files
on a single canvas, effectively merging individual images
together to form a larger picture. (Panoply allows only two
files to be be combined).
Provided McIDAS-V recognises a SAF file as having fullgeo-location information, it is a competent viewer, although
I think that it is poor at handling a simple two dimensional
image and would not recommend it for this purpose.
Weather and Climate Toolkit(https://www.ncdc.noaa.gov/wct/)
I have only included the Weather and Climate Toolkit(WCT) from NOAA because I was aware of the viewer. It

has a heavy emphasis towards US products. Unless I havemissed something obvious, it will only display files whichcontain full geo-location information that it can recognise.
In addition, the only map projection that it supports
appears to Plate Carrée, limiting its use for viewing polar
regions. However, its use may be of interest outside the
SAF product area.
ESA SNAP(https://step.esa.int/main/download/snap-download/)
The Sentinel Application Platform (SNAP) is provided by
the European Space Agency, and although it is primarily
aimed at the Sentinel series of satellites, it can also
process netCDF and HDF files from a wide variety ofother sources. I found it to be a complex application that
required a considerable amount of work and understanding
to produce relevant images and I think that it is aimed at
the professional user who requires good analytical tools. I
do not use it on a regular basis.
In contrast to the three previously described applications(Panoply, McIDAS-V and WCT), SNAP does not have any
built-in basemaps as far as I know and I needed to loada shapefile to add coastline data to an image. As withthe other viewers, the coastline data is only shown withfiles that SNAP recognises as containing full geo-location
information using the Geographic Co-ordinate System.
SNAP does not appear to recognise geo-location in files
using the Projection Co-ordinate System unless I havemissed something.
HDFView(https://www.hdfgroup.org/downloads/hdfview/)
HDFView is an elegantly simple tool provided by the HDF
Group for viewing HDF files. It can also be used as aviewer for netCDF4 files (applies to SAF netCDF products
as far as I can tell) as the dataset inside this file type isstored using the HDF5 hierarchical format.
Variables are selected from a data tree and can be viewed
as a spreadsheet or as a flat two dimensional image witha limited range of colour palettes. There is no basemap
facility.
Scientific Analysis and Presentation
I have included MATLAB, R and GMT in this category
as they are mentioned in training material produced bya couple of SAF providers as a method of producing
images. I suspect that one or more of these applications
has been used to generate images that are available
on some of the SAF websites but they all need suitable
scripts for operation. I have no personal experience of
these applications and regard them as best suited for
professional use.
Geographic Information Systems (GIS)
I find the term GIS a bit woolly but it seems to encompass
creating, managing, analysing and mapping geospatial
data and this includes images with geo-referencing
properties.

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QGIS
(https://qgis.org/en/site/index.html)
QGIS is probably one of the best known free andopen-source GIS applications and I did perform a few
experiments with it. I was able to import and display anumber of SAF related netCDF and HDF5 files but the
sheer complexity of the application means that I did notuse it as a day to day SAF viewer.
ILWIS 386
https://www.itc.nl/about-itc/organization/scientificdepartments/water-resources/software-tools-models/
ilwis3-and-toolbox-plugins/
ILWIS 386 is another fully-featured free GIS application(Windows only) from the University of Twente and one
which I would not normally pursue. However, a feature thatis of particular interest is a plug-in called GEONETCast
Toolbox.
GEONETCast is a global meteorological dissemination
service that includes data from EUMETCast in its
broadcast streams. The toolbox is able to ingest files
exactly as received by a EUMETCast Tellicast client andconvert them into the proprietary ILWIS image format,
adding geo-referencing along the way if required. SomeSAF products are included in the toolbox catalogue andI believe that it is possible for non-programmers to add
additional products if they are missing. For one SAF
product, which I shall cover later in this article, the toolbox
was the only application that could provide the image that
I sought.

structure and full geo-referencing using the Geographic
Co-ordinate System. As a result, I established that all thegeneric viewers are able to provide OSI images completewith basemap where the capability exists.
Combining Files (NCO)
Two of the OSI products designated as OSI-204-c andOSI-208-b (search on EUMETSAT Product Navigator)
are derived from Low Earth Orbit (LEO) satellites andprovide global coverage. The data is supplied in chunks
as a sequence of files, each containing three minutes
worth of information, with up to 480 files per day. Whilsteach file could be viewed individually, I wanted to combine
them in some way to produce a single global image.
Using a generic viewer to do this was not practical so the
only obvious alternative was to combine all the individual
netCDF files into a single larger one.
I identified two toolsets that specialise in manipulating
netCDF files which were the Climate Data Operators(CDO) and netCDF Operators (NCO) in the hope that oneof them would be able to perform the spatial combination.
Although both toolsets are designed for use under Linux,
my initial research suggested that they could also be used
under Windows. General purpose software could also be
used to combine files but I was unable to find a suitable
script and do not currently have the knowledge to produce
one but I’ll keep looking.

The ILWIS 386 core application and Toolbox plug-in comewith comprehensive documentation indicating that they canbe used for a wide range of image processing functions
with EUMETCast products in general but I have yet toexperiment with these.
General Purpose Software
The use of general purpose software can obviously
provide any solution but it relies on having a suitable
script. In the Earth Observation field, Python now appears
to be the language of choice, especially as pre-existing
software libraries for manipulating netCDF, HDF, GRIB and
BUFR datasets now have Python interfaces.
Viewing SAF products
In summary, my goal was to visualise all the SAF products
from the providers listed in Table 1 against a basemap ofcoastlines using a Windows based system. To achievethis, I will describe the software applications and methods
that I used. With ease of use in mind, my first choice of
application(s) were those at the top of Table 2 and I would
then work my way down the table if these proved to beineffectual. I did not consider the applications listed under
the Scientific Analysis and Presentation category as these
seemed better suited to professional users..
Ocean & Sea Ice (OSI)
I have started with the OSI products as I think that these
are the easiest to visualise. The data is delivered as
netCDF4 files with a straightforward two dimensional

Figure 1 - An OSI 10 m global wind image derived from 100+
individual files using NCO and generated with Panoply.
The red dot is Hurricane Larry

To cut a long story short, I rejected CDO because it could
not be used with Windows as far as I could tell and NCO
was available as a native Windows build. I also establishedthat NCO could combine files spatially following
experiments with the Linux version and a BASH shell
script to automate the process. But when I tried to replicate
the operation on the Windows build using a batch file, I

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ran into problems. Firstly, the Windows command shell
does not have native support for a feature called ‘wildcard
expansion’, although I was able to find a workaround.
More seriously, the Windows build of NCO did not properly
replicate the Linux version and proved to be unusable
in my application. I then discovered that NCO had beenreleased as a Cygwin package so I experimented withthis option and received excellent results. The Cygwin
version worked perfectly and also allowed me to use myoriginal BASH shell scripts under Windows with necessarychanges to path names. An example of an image derived
from combining multiple files is shown in Figure 1.
The Windows Subsystem for Linux (WSL) could be used
for both CDO and NCO but this solution seemed likeoverkill to me and in any case, my version of Windows
didn’t support it.
Another product designated as OSI-205-a covers the northand south high latitude regions and is also transmitted
as a sequence of three minute files. These can also be
combined using NCO to form a single netCDF file.
Combining Files (McIDAS-V)
The OSI product designated as OSI-410 is derived from
LEO satellites and provides an excellent view of the sea
ice concentration around the poles. The received files
contain either a half orbit or a full orbit’s worth of data
depending on the particular satellite type. As each file only
covers a limited segment of the polar regions, they need tobe combined to provide a full picture of the ice coverage.
I was unable to combine the files using the NCO toolset(I received an error message that I could not resolve) so I
looked for an alternative solution. I was aware that a daily
composite image was already transmitted but I wanted tofind out how to do it myself as an academic exercise.

Figure 2a - OSI Arctic polar ice coverage image (incomplete)derived from multiple files containing data from AMSR-2
instrument on GCOM satellite and generated with McIDAS-V

As mentioned earlier in the article, McIDAS-V is able toload and display multiple files on a single canvas thereby
combining the images on screen rather than through file
manipulation. In practice, I would suggest that this only
works for a limited number of individual files but is perfectly
feasible with the numbers involved for the OSI-410
product.
For my initial experiments, I created a viewing panel witha basemap and loaded each file manually, but this method
quickly became very tedious when dealing with more thanhalf a dozen or so. To speed up the process, I used thescripting capability of McIDAS-V and prepared a couple ofscripts using the Jython shell to ingest files automaticallyand project the resultant images on to baseline mapsof the polar regions. Two partially populated images areshown in Figures 2a and 2b.
Land Surface Analysis (LSA)The LSA data is delivered as HDF5 files with a twodimensional structure and no geo-reference information.
If a basemap is required for the images, the viewing
application is expected to identify the product contained ina file and provide the missing geo-reference informationfrom its own resources. This is possible because theviewpoint for a given product type is constant so theposition of each pixel relative to the Earth remains fixed.

Figure 2b - OSI Antarctic polar ice coverage image (incomplete)derived from multiple files containing data from AMSR-2
instrument on GCOM satellite and generated with McIDAS-V

Products distributed up to 2015 were constrained byprocessing limitations as described in the following
quotation extracted from an LSA document.
‘Due to computational limitations in the early days of
the LSA SAF, the MSG derived products generated in
the period between 2004 and 2015 were processed
into 4 geographical areas within the MSG-Disk. Since
2016, all MSG derived products are produced andavailable for the SEVIRI full disk. However, someproducts are still distributed via EUMETCast split
into the former 4 geographical regions, mainly due tobandwidth restrictions on the broadcast services’.

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The four regions are Europe, Northern Africa, Southern
Africa and South America.
The HDF Viewer from David Taylor was able to visualisesome LSA products including the regional versions whilst
adding coastline and country boundary outlines but,unfortunately, was not able to cope with the majority of thefull disk images. I think that there was a change to the fileformat for these that the viewer was unable to handle.
I was able to view all of the LSA products (with two
exceptions) in a simple two dimensional format without
basemap using Panoply and HDFView. The two exceptions
were global products derived from LEO satellites (productreferences H32 and LSA-002) which weighed in with aneye-watering resolution of 36000 x 18000 pixels and could
not be handled by the these two viewers. However, the
ESA SNAP viewer (as suggested by the LSA SAF website)
was able to produce images. Note that the H32 product isdelivered by the LSA SAF on behalf of the H SAF.
LSA Geo-referencing
As my goal was to visualise all products including
basemaps, I was stubborn enough to try and find a
way around the limitations mentioned in the previous
section. Further research found a Python script in asoftware repository (https://gitlab.com/joao.macedo/
msg_hdf5_to_netcdf) that converted the MSG derived
products in HDF5 format into netCDF4 files, adding ageostationary projection co-ordinate system along the way.
The resultant images could be projected on to basemaps
with Panoply, WCT and QGIS. McIDAS-V had trouble
with correct interpretation for some reason but I was able
to compensate by modifying an attribute in the resultant
netCDF file using the NCO toolset. ESA SNAP did notrecognise the projection co-ordinate system so there wasno advantage in using this viewer with the netCDF file. An
example of the result is shown in Figure 3.
Two of the MSG derived products generated an error
with the Python script so I investigated further and foundthat the cause was surprisingly simple. The metadata
contained a single character that was not UTF-8 compliant,causing the Python script to abort. I wrote a very simple
Python script to modify the character in the HDF5 file prior
to the conversion process and the problem was fixed.
For the two global products, I used two different solutions.
The H32 snow product has only 6 possible values per
pixel, one of which is water. By creating a custom colour
palette in ESA SNAP that allocated a unique colour (suchas blue) to the water areas, the coastlines were clearlydelineated and I regarded a basemap as unnecessary. An
example of the result is shown in Figure 4.
For the LSA-002 product, I used the ILWIS 386 GIS in
conjunction with the GEONETCast Toolbox to produce an
ILWIS image file and accompanying geo-reference file. I
was then able to view the image using ILWIS 386 and add
coastlines, grid lines and colour interpretation bar at will.
An example of the result is shown in Figure 5.
The GEONETCast catalogue is not confined to LSA-002
and is able to process other LSA products as well.

Figure 3 - LSA full disk Land Surface Temperature generated
with Panoply after conversion with Python script.

Figure 4 - EPS Daily Snow Cover generated with ESA SNAP.
Original resolution was 36000 x 18000 pixels.

Figure 5- EPS Daily Land Surface Temperature generated withILWIS 386 and GEONETCast Toolbox. Original resolution was
36000 x 18000 pixels.

Hydrology SAF (H SAF)
The H SAF data is delivered as netCDF, BUFR and
GRIB files and some products are provided as netCDF
and BUFR in parallel. I don’t know how long this dual
arrangement will continue as H SAF has indicated that it ismoving towards netCDF and discontinuing BUFR at somepoint.

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NetCDF files are delivered with a straightforward two
dimensional structure and full geo-referencing using theGeographic Co-ordinate System. I established that all thegeneric viewers are able to provide OSI images completewith basemap where the capability exists. For BUFR files,
the BUFRdisplay viewer was the one that I used.
For GRIB files, my first choice was David Taylor’s GRIB
Viewer as it is aimed towards EUMETCast products andprovided a basemap. For one product that I tried witha designation of H14, it was not able to open the file,possibly because it lacked the necessary tables. Of thegeneric viewers, Panoply, McIDAS-V and WCT werealso capable of viewing GRIB files although there wasa potential quirk with precipitation products H03 andH05. The range of valid data within these two products
included a rainfall value of zero and this can occupy a lotof the total dataset. The generic viewers populated theimage with areas covered by this zero rainfall, adding a
lot of extraneous detail that detracted from active rainfall
locations. This did not happen with the GRIB Viewer andI assume that it applies a filter to the data to remove zerorainfall areas from view. In addition, the generic viewers
also displayed the default rainfall values as kg/m2 persecond, or kg per m2 which is not particularly meaningful
although units can be changed in McIDAS-V.
I haven’t found a way to filter the data on the genericviewers so that they ignore zero values but I have founda solution in colour table configuration. McIDAS-V has abuilt-in colour table editor that includes a transparency
property and allows a background to ‘shine through’defined colour ranges. This property can be used tohide the zero rainfall areas or any value below a given
threshold. With Panoply and WCT, the range of displayed
values can be altered but the full colour table then applies
to this new range and they don’t have a table editor. I thinkthat the best solution here is to try and find a colour tablethat gives the best visual appearance.
Combining Files (McIDAS-V & BUFR)
H SAF files for product H01 and H02 contain data
covering a partial orbit of a LEO satellite and the mostinformative images are provided by viewing multiple files
simultaneously. For the time being, these files are available
in both netCDF and BUFR format. BUFRdisplay alreadyhas the ability to view multiple files so no further action
is needed for this viewer. As far as the netCDF files areconcerned, I have not managed to combine them using the
NCO toolset and I don’t know if this is even possible. My
immediate solution was to combine them with McIDAS-V,
employing the same method that I used for the OSI-410
product previously mentioned and assisted by a Jython
script. Because the images derived from the individual files
overlapped frequently, I needed to adjust the associatedcolour table to stop “wash-out” in the overlapping areas
and further work is needed for this aspect. An example of
the result is shown in Figure 6.
I note that product H08 also uses parallel transmissionof netCDF and BUFR files but I have yet to investigate
the merging of netCDF files in this instance. I don’t thinkthat the NCO toolset can cope because of the variation indimension sizes between each file.

Figure 6 - H SAF Precipitation Rate at Ground derived fromDMSP satellites in multiple passes generated by McIDAS-V

NowCasting (NWC)
The NWC products available over EUMETCast relate tocloud properties and are split into two distinct streams Geostationary(GEO) and Polar Platform System (PPS)
represented by LEO satellites. Unusually, the NWC
products do not have their own EUMETCast channel andthe data is disseminated over Data Channel 3 for GEO
products and Data Channel 1 for PPS products (thesechannel names will change in 2022).
GEO
The GEO data is delivered as netCDF4 files with a twodimensional structure and a geostationary projection
co-ordinate system that was not recognised by any of thegeneric viewers. Two products are available—one withcloud type and the other with cloud altitude, pressure andheight properties. Each property also has an associatedcolour palette included in the product file. I was able toview the products in a simple two dimensional format
without coastlines using Panoply, HDFView and ESA
SNAP although none of these recognised the colour
palette data and used their own defaults instead.
Looking more closely at the netCDF file, I sensed thatextra data was needed to allow the generic viewer torecognise the projection co-ordinate system. Using NCO,
I added some extra metadata to a GEO file and foundthat Panoply was then able to project the images on toa basemap correctly but other viewers could not. This isprobably not surprising as I was manipulating netCDF files
without much clue as to what I was doing, but it did showthat there was room for more experimentation.
Further research revealed that a tool called NWCPY (thisis a pure Python script) is available via the NWC SAF
website. This script generates images from GEO products
exactly like those shown on the website (https://www.
nwcsaf.org) including the colour interpretation bar at thebottom.
PPS
The PPS data is delivered as netCDF4 files over the
EUMETCast EARS channel with a two dimensional
structure and a geographic projection co-ordinate system.
Each file represents one minutes worth of data. However,
the geographic co-ordinates are only supplied for one pixel

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Figure 7 - NWC PPS Cloud Type derived from Metop-B generated by Python using SatPy package and based on script provided by
Ernst Lobsiger in Pytroll Starter Kit.

in every five for both the X and Y directions, presumably
to save bandwidth. The same two products as GEO areavailable.

and HCHO. The data is delivered as both BUFR and HDF5
files with an odd structure. The SO2 data should be usefulin the monitoring of volcanos.

To produce a decent image, it was clear that I needed tojoin a number of files together and provide a basemap
otherwise it would be extremely difficult to geo-locate cloud
images if no recognisable land features were visible. The
partial nature of the co-ordinates meant that none of thegeneric viewers was able to supply a basemap, so the only
answer was going to be general purpose software and thatwas beyond my capabilities. I could find nothing on thewebsite of any help. Back to research for an answer.

For viewing the BUFR files, I used BUFRdisplay as the
go-to application.

It turns out that PyTroll was started by one of themeteorological organisations that produces the NWC SAF
data and that the Satpy package has a reader for the NWC
PPS format. Sample skeleton scripts for the PPS products
are available on the Pytroll examples software repository(https://github.com/pytroll/pytroll-examples) under nwcsaftutorials. I couldn’t open the relevant Jupyter Notebook file
directly so I resorted to the online nbviewer instead.
For a very good article on the history of PyTroll, I canrecommend a paper in the Bulletin of the American
Meteorological Society, July 2018. (https://journals.
ametsoc.org/view/journals/bams/99/7/bams-d-170277.1.xml?rskey=S5M8pG&result=1).
Using PyTroll and building on these scripts to define
regions of interest and image decoration would have been
beyond my capability were it not for the excellent Pytroll/
SatPy Starter Kit information provided by Ernst Lobsiger(thanks Ernst) and published on the MSG-1 Groups
website. I eventually generated combined day/night scripts
to produce cloud type images for METOP-B and NOAA‑19,
the two satellites currently providing PPS products. An
example image is shown in Figure 7.
Atmospheric Composition (AC)The final SAF products that I tried to were thosedisseminated by the AC SAF. This provides information
about trace atmospheric gases such as ozone, NO2, SO2,

I determined that some of the HDF5 files had a one
dimensional structure representing a data stream provided
by a scanner that was swinging from side to side, and it
was clear that none of the generic viewers, or any nonbespoke application for that matter, would be able tointerpret the data. This was a definite general purpose
software task so I embarked on a research program yetagain to find a solution.
Eventually, I found some suitable Python scripts on a
EUMETSAT software repository (they don’t make it easy)at (https://gitlab.eumetsat.int/eumetlab/atmosphere/
atmosphere). I have only managed to produce a small
image of a single file on a map background to date so thisSAF is very much a work in progress.
Conclusion
My quest to visualise as many SAF products as possible
has been an interesting journey. Some of the products are
disseminated only once per day and so there are a numberthat I have probably not tested but I hope to investigate
them at some point.
For BUFR and GRIB files, I have concluded that thebest viewing applications are BUFRdisplay and GRIB
Viewer respectively with a small amount of backup fromgeneric viewers for the latter. For netCDF and HDF5 files,
however, the situation is completely different. The selfdescribing nature of these file types means that there canbe a wide variation in their structure—a bit like defining thegrammar and vocabulary for a language and then allowing
authors to write whatever they want. To stretch the analogy
further, one or more of the generic viewers can provide an
abstract (and sometimes more) but to guarantee reading
the complete text, general purpose software such as
Python or specialist applications are needed.

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The Calm Before Storm Arwen

It’s the early hours of November 26, 2021, a cool, cloudless night less than 24 hours before the arrival of Storm
Arwen. NOAA’s Suomi-NPP satellite imaged this scene, picking out dozens of towns and cities as bright white spots
using its VIIRS Day/Night Band. The following day, winds of up to 150 kph scoured the eastern coasts of Scotland
and northeast England, downing trees, cutting communications, and leaving thousands of households without power.
Image: NASA Worldview Snapshots (https://wvs.earthdata.nasa.gov/)

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