Aviation Meteorologist, Col.(ret) Greek Air Force
@ivo
Fantastic!
Many thanks to Ivo and the windy team! Aim High!
Description needed https://community.windy.com/topic/3361/description-of-weather-overlays
Q: the color overlay in INFRA+ has to do with
cloud top temperature,
precipitation estimate or
instantaneous precipitation rate ?
@ivo
A small suggestion:
The "donation symbol" is not a wise decision.
You use the same symbol for "fullscreen mode".
I think those symbols are better
Source:
https://www.nesdis.noaa.gov/content/celebrating-60-years-world’s-first-weather-satellite
https://vlab.ncep.noaa.gov/web/nws-heritage/-/the-satellite-era-begins
On 1 April 1960, NASA launched the world’s first weather satellite named TIROS-1 (Television Infra Red Observation Satellite). Although the mission was short lived (only 78 days) TIROS-1 sent back 19,389 usable pictures, proving the worth of weather observing satellites to the world and opening the door for the weather systems of the future.
The first image from the satellite was a fuzzy picture of thick bands and clusters of clouds over the United States.
“It really was a milestone in the history of weather observation,” said Stephen Volz, Ph.D., Assistant Administrator of NOAA’s Satellite and Information Service.
Today, with the next generation of environmental observation satellites in orbit we are continuously improving our weather monitoring and prediction with state-of-the-art data and imagery. These satellites are also significantly enhancing our understanding of the Earth as a whole system.
“TIROS was just the first step,” Volz added. “Now we're starting to peel back those environmental layers and understand how they connect together. We can see vegetation health from space and measure how warm the ground is. We can see fires around the world and determine the altimetry of water and waves from space.
All of this is based on what we learned—and what we saw—with our first glimpses from TIROS.”
TIROS Technical Control Center at the Goddard Space Flight Center, Greenbelt, Maryland, USA (File photo, 1964). Credits: NASA's Goddard Space Flight Center
One of the first images returned (May 9, 1960) by TIROS-1. Superimposed on the cloud patterns is a generalized weather map for the region.
The comparison of the progress in meteorological imaging. Left: image taken by the TIROS 1 satellite, 1960. Right: the same region imaged by the satellite NOAA 15, 2000.
... and today
Today, the day/night terminator line is parallel to the axis of the Earth
and to lines of longitude.
@TZ
is there a color scale? e.g. blue < -20C, red < -30C etc
It would be great if the picker shows (cloud top) temperature
Aeolus is a polar-orbiting satellite which sends laser light into the atmosphere and measures the backscatter to obtain information on winds in the direction perpendicular to the satellite’s path.
ECMWF started assimilating wind data from the European Space Agency's ground-breaking Aeolus satellite operationally on 9 January 2020 after tests showed that they significantly improve weather forecasts.
Aeolus was launched in August 2018 to test the usefulness of direct wind profile observations from space for numerical weather prediction. It works by measuring the backscatter of laser light from air molecules (‘Rayleigh-clear’ data) and from clouds and aerosols (‘Mie-cloudy’ data).
The Aeolus satellite passed close to Hurricane Dorian as the storm stalled over the Bahamas, as shown in this image from NASA’s Aqua satellite taken at 1805 UTC on 1 September 2019. The red line has been superimposed to indicate Aeolus’s path. The Aeolus wind data for that path and beyond, from about 6°N to 42°N, are shown below.
Aeolus horizontal-line-of-sight (HLOS) wind observations, measured in the direction of the laser beam and projected onto the horizontal plane, on 1 September 2019 between about 6°N and 42°N, including the path near Hurricane Dorian shown in the satellite image above. The data are a combination of Rayleigh-clear and Mie-cloudy data.
The Aeolus observations being assimilated come from a second laser switched on in June 2019 after the first laser had lost a fraction of its power. The second laser has been found to deliver more stable power at sufficiently high intensity.
Tests carried out at ECMWF have demonstrated that the impact of the new observations on forecasts in the southern hemisphere and the tropics is comparable to that of some other major components of the Earth observing system.
Several other numerical weather prediction centres have also found big improvements in weather forecasts when assimilating Aeolus data in test experiments. It is highly unusual for a completely new type of satellite data to be ready for operational use as early as 16 months after launch.
Successful bias correction is an important part of optimising the use of satellite data. Over the last 12 months, ECMWF scientists, in close collaboration with engineers and scientists from DLR, DoRIT, ESA, KNMI and Météo-France, have made big strides in understanding Aeolus biases.
Details on forecast improvements resulting from the use of Aeolus data and on continuing efforts to improve the bias correction can be found in a previous news article. The main points are reproduced below.
To determine the initial conditions for weather forecasts, Earth system observations are combined with short-range forecast information in a process called data assimilation.
An important question scientists ask of any new Earth system observations is the impact assimilating them has on the accuracy of those short-range forecasts as well as on medium- and longer-range forecasts.
Tests show that, when Aeolus data are assimilated, the short-range forecasts used in the data assimilation system are much improved: they are significantly closer to other wind, temperature and humidity observations (including aircraft, radiosonde and satellite data) than when Aeolus data are not assimilated. This is true especially in the southern hemisphere and the tropics.
The charts show a reduction of up to 1.5% in differences between radiosonde, profiler and aircraft wind observations and short-range forecasts used in the data assimilation system as a result of assimilating Aeolus data in the tropics (left) and in the extratropical southern hemisphere (right). The differences without the assimilation of Aeolus data, expressed in terms of the standard deviation, are represented by the 100% mark. The horizontal lines represent 95% confidence intervals. The experiment covers the period of 2 August to 22 October 2019.
ECMWF’s main mission is to produce high-quality medium-range forecasts, between three to ten days ahead. A crucial question for the Centre’s scientists is thus what impact the assimilation of Aeolus data has on such forecasts.
Here, too, the results are very encouraging: there are clear improvements in weather forecasts throughout the medium range. The improvements can be found mainly in the tropics and the southern hemisphere, which are less well covered by conventional wind observations than the northern hemisphere.
These plots show how the assimilation of bias-corrected Aeolus data (Rayleigh-clear and Mie-cloudy) reduces wind forecast errors (blue shading) in large parts of the southern hemisphere and the tropics throughout the troposphere and beyond (10 hPa corresponds to about 30 km altitude). In the northern hemisphere, forecasts improve mainly in the polar region. Cross-hatching indicates statistical significance at the 95% level. The experiment covers the period from 2 August to 18 October 2019.
Another important test is how the impact of assimilating Aeolus data compares to the impact of assimilating other Earth system observations.
“We have found the overall impact of Aeolus data on forecasts in the southern hemisphere and the tropics to be comparable to that of data from some other major components of the global observing system,” says ECMWF’s Mike Rennie, whose work on the data is funded by ESA.
Aeolus wind data compare well with data from other parts of the global observing system, such as Atmospheric Motion Vectors, satellite-to-satellite radio occultation data, and satellite data from infrared sensors.
In the northern hemisphere, the effect of assimilating Aeolus data on forecasts is more uneven than in the southern hemisphere.
“This is partly because much of the northern hemisphere is already relatively well observed,” says Lars Isaksen, the Head of the Actively Sensed Observations Group at ECMWF. “But we suspect that the complex pattern of Aeolus data biases in the northern hemisphere might also play a role,” he adds.
“We have been able to identify and correct some of these biases successfully, but there is scope for further improvements, due to a recent breakthrough.”
Patient scientific detective work carried out by Mike, in collaboration with other scientists, has shown that Aeolus biases are closely correlated with small variations in the temperature distribution across the large mirror used in the Aeolus instrument’s telescope.
“This finding will enable us to refine our bias correction, since those temperatures are measured in space and available in real time,” Mike says.
“Aeolus engineers and scientists are now investigating why such temperature differences cause large wind biases and if the mirror temperatures can be controlled better. A better understanding will be very valuable when designing and building a potential follow-on Aeolus instrument.”
Biases in Aeolus wind data have been found to be closely correlated with tiny temperature variations across the 1.5 m diameter mirror which forms an important part of the Aeolus instrument. A 0.1°C change in temperature difference leads to a change in wind bias of around 5 m/s.
@ivo
In the latest version of windytv there are more overlays (e.g. cloud tops, frz altitude, visibility).
So, some more descriptions needed.
Today, 23 Mar. is the World Meteorology Day.
This year's theme is: "Weather-ready, climate-smart".
Let's celebrate!
@gillie-0
Sounding is a diagram that shows the vertical distribution
of temperature, humidity and wind into the atmosphere.
Usually the observations are made by radiosondes
(instruments carried into the atmosphere by a weather balloon).
Weather models can give us forecast data of the same parameters
so we can prepare "forecast soundings".
Soundings are used by (glider) pilots to know thermals, winds aloft, icing forecast etc
and by meteorologists (and weather enthusiasts) for rain/snow forecast,
fog forecasting, turbulence, cloud bases/tops, thunderstorms etc
A medicane (A Mediterranean tropical-like cyclone)
expected to form west of Grecce
on Friday 28 Sep. 2018.
Windy forecasted another one last November (2017)
https://community.windy.com/topic/4935/medicane
@You-Adam-Anir
try https://gis.ncdc.noaa.gov/maps/ncei/summaries/global
P.S. for "big" countries (e.g. Russia, USA, Canada ...) daily average temperature is meaningless.
.... radar coverage
......
The area of Istria is covered by the Croatian radar in Puntijarka
but this radar seems inactive since 23 Apr. 2020.
https://meteo.hr/podaci_e.php?section=podaci_mjerenja¶m=radari&el=puntijarka
Istria is not covered by Croatian and Sebian wx. radars.
Windy radar map provides radar data from the adjacent countries.
INPUT
OUTPUT
Slovenian meteo. service seems do not provide data
for the area beyond the red line.
Also read https://community.windy.com/topic/9700/radar-picture-at-the-tip-of-istria?_=1589962972001
@idefix37
Yes it is! (according to Windy's forecasts!)
@Korina
I used density altitude plugin.
@vsinceac
Metars always include sign. phenomena (and rain) group.
In the screenshot
we see thunderstorm with rain on Sunday 17 May afternoon.
HELX metars are:
METAR HELX 172300Z 12003KT 6000 SCT020 29/14 Q1006 NOSIG=
METAR HELX 172200Z 16004KT 6000 SCT020 32/12 Q1007 NOSIG=
METAR HELX 172100Z 08008KT 6000 BKN020 34/12 Q1007 NOSIG=
METAR HELX 172000Z 17007KT 6000 BKN020CB 34/13 Q1007 NOSIG=
METAR HELX 171900Z 03006KT 6000 BKN020CB 34/13 Q1007 NOSIG=
METAR HELX 171800Z 03004KT 6000 BKN020CB 32/17 Q1006 NOSIG=
METAR HELX 171700Z 01016KT 2000 SA BKN020CB 32/17 Q1006 NOSIG=
METAR HELX 171600Z 26012KT 2000 TSSA BKN020CB 36/16 Q1004 NOSIG=
METAR HELX 171500Z 25012KT 9999 TS SCT020CB 36/16 Q1004 NOSIG=
METAR HELX 171400Z 23008KT 9999 TS SCT020CB 40/14 Q1004 NOSIG=
SPECI HELX 171335Z 22012KT 9999 TS SCT020CB 42/13 Q1004 NOSIG=
METAR HELX 171300Z 06008KT 9999 SCT020 43/17 Q1004 NOSIG=
METAR HELX 171200Z 08010KT 9999 FEW030 42/16 Q1005 NOSIG=
SYNOPS are
Conclusion:
according to observations (wx. reports)
at 17/1335Z there is a speci (-al report) of TS (thunderstorm heard)
at 14Z and 15Z the same.
at 16Z, TS and visibility droped down to 2 km due to SAnd (not due to rain).
at 17Z, visibility remains at 2km due to SAndstorm. No thunder heard.
at 18Z, visibility improved to 6 km.
From SYNOPs the precipitation amount is 0.0 mm.
That means no rain recorded (although some traces from droplets may occur).
It was a dry thunderstorm https://en.wikipedia.org/wiki/Dry_thunderstorm
and the visibility were reduced due to sandstorm.
I think there is a minor bug in Windy's decoder.
On Sunday afternoon it shows (erroneously) thunderstorm with rain.
The render read TS and translated it with a wrong symbol.
