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earth

a visualization of global weather conditions
forecast by supercomputers
updated every three hours

 

ocean surface current estimates
updated every five days

 

ocean surface temperatures and
anomaly from daily average (1981-2011)
updated daily

 

ocean waves
updated every three hours

 

aurora
updated every thirty minutes

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licensing

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translations

help translate this site by visiting translate.nullschool.net

Community Facebook Page
Author Cameron Beccario @cambecc
Free Version of Source github.com/cambecc/earth
Modules D3.js
node.js
Weather Data GFS (Global Forecast System)
EMC / NCEP / NWS / NOAA
Ocean Currents Data OSCAR
Earth & Space Research
Sea Surface Temperature RTGSST (Real Time Global Sea Surface Temperature)
MMAB / EMC / NCEP / NWS / NOAA
Ocean Waves WAVEWATCH III
MMAB / EMC / NCEP / NWS / NOAA
Aerosols and Chemistry GEOS-5 (Goddard Earth Observing System)
GMAO / NASA
CAMS (Copernicus Atmosphere Monitoring System)
Copernicus / European Commission + ECMWF
Aurora OVATION
SWPC / NCEP / NWS / NOAA
Processing script written by Stephanie Hamilton (profile)
GRIB/NetCDF Decoder UCAR/Unidata THREDDS
Geographic Data Natural Earth
Hosting CloudFlare
Amazon S3
Fonts M+ FONTS
Google Noto Fonts
Font Awesome
Translation Management OneSky
Color Scales ColorBrewer2.org
Kindlmann Linear Luminance
MYCARTA
Dave Green's cubehelix
Waterman Butterfly watermanpolyhedron.com
Prototype 東京風速
Inspiration HINT.FM wind map

atmospheric pressure corresponds roughly to altitude
several pressure layers are meteorologically interesting
they show data assuming the earth is completely smooth
note: 1 hectopascal (hPa) = 1 millibar (mb)

1000 hPa 00,~100 m, near sea level conditions
850 hPa 0~1,500 m, planetary boundary, low
700 hPa 0~3,500 m, planetary boundary, high
500 hPa 0~5,000 m, vorticity
250 hPa ~10,500 m, jet stream
70 hPa ~17,500 m, stratosphere
10 hPa ~26,500 m, even more stratosphere

the "Surface" layer represents conditions at ground or water level
this layer follows the contours of mountains, valleys, etc.

 

overlays show another dimension of data using color
some overlays are valid at a specific height
while others are valid for the entire thickness of the atmosphere

Wind wind speed at specified height
Temp temperature at specified height
RH relative humidity at specified height
WPD Instantaneous Wind Power Density
measure of power available in the wind: ½ρv3, where ρ is air density and v is wind velocity
TPW Total Precipitable Water
total amount of water in a column of air stretching from ground to space
TCW Total Cloud Water
total amount of water in clouds in a column of air from ground to space
3HPA 3-hour Precipitation Accumulation
amount of precipitation over the next three hours
CAPE Convective Available Potential Energy from Surface
indicates the buoyancy of air, a measure of atmospheric instability and predictor of severe weather
MSLP Mean Sea Level Pressure
air pressure reduced to sea level
MI Misery Index
perceived air temperature as combination of heat index and wind chill
SST Sea Surface Temperature
temperature of the ocean surface
SSTA Sea Surface Temperature Anomaly
difference in ocean temperature from daily average during years 1981-2011
HTSGW Significant Wave Height
roughly equal to mean wave height as estimated by a "trained observer"
pCO2 Sea Surface CO2 Partial Pressure
FGCO2 Sea-Air CO2 Flux Density
the rate of movement of molecules across a unit area
COsc Carbon Monoxide Surface Concentration
the fraction of carbon monoxide present in air at the earth's surface
CO2sc Carbon Dioxide Surface Concentration
the fraction of carbon dioxide present in air at the earth's surface
SO2sm Sulfur Dioxide Surface Mass
amount of sulfur dioxide in the air near the earth's surface
DUex Dust Extinction
the aerosol optical thickness (AOT) of light at 550 nm due to dust
SO4ex Sulfate Extinction
the aerosol optical thickness (AOT) of light at 550 nm due to sulfate
PM1 Particulate Matter < 1 µm
mass of atmospheric particles with a diameter less than 1 micron
PM2.5 Particulate Matter < 2.5 µm
mass of atmospheric particles with a diameter less than 2.5 microns
PM10 Particulate Matter < 10 µm
mass of atmospheric particles with a diameter less than 10 microns

about ocean waves

Significant Wave Height is the average height of the highest 1/3 of waves at a particular point in the ocean. There's a great writeup here describing what this means.

Peak Wave Period is the (inverse) frequency of the most energetic waves passing through a particular point, whether wind generated or swells. Certainly, there are many more groups of waves moving through an area, each in different directions, but trying to show them all rapidly becomes complex. Instead, we show the one wave group contributing the most energy. This has the effect, though, of creating "boundaries" between regions of ocean where the #1 wave group suddenly switches to second place. Often these boundaries represent swell fronts, but other times they are just artifacts of the ranking mechanism.

about CO2 concentrations
for dates earlier than 2017-01-24 04:30 UTC

While implementing the visualization of CO2 surface concentration, I noticed the NASA GEOS-5 model reports a global mean concentration that differs significantly from widely reported numbers. For example, from the run at 2015-11-23 00:00 UTC, the global mean is only 368 ppmv whereas CO2 observatories report concentrations closer to 400 ppmv. GEOS-5 was constructed in the 2000s, so perhaps the model does not account for accumulation of atmospheric CO2 over time? This is simply speculation. I am just not certain.

To bring the GEOS-5 results closer to contemporary numbers, I have added a uniform offset of +32 ppmv, increasing the global mean to 400 ppmv. This is not scientifically valid, but it does allow the visualization to become illustrative of the discussion occurring today around atmospheric CO2. Without question, I would welcome a more rigorous approach or an explanation why the GEOS-5 model produces the data that it does.

From 2017-01-24 04:30 UTC, this adjustment is no longer necessary because GEOS-5 appears to have been upgraded.

disclaimer

GEOS-5 data (covering all Chem and Particulates layers) comes with the following disclaimer: Forecasts using the GEOS system are experimental and are produced for research purposes only. Use of these forecasts for purposes other than research is not recommended.

about aerosols and extinction

An aerosol is air containing particles. Common particles are dust, smoke, soot, and water droplets (clouds). These particles affect sunlight primarily through absorption and scattering, which combine to reduce the amount of light reaching the ground. This loss of light as it passes through the atmosphere is called extinction.

One common measure of extinction is aerosol optical thickness (AOT), which is (the log of) the ratio between the power of incoming light and the power of transmitted light. This helps us understand how "thick" the air is with particulates.

keyboard shortcuts

e show the menu
escape close dialog/menu
k go forward one time step
shift-k go forward several time steps
j go backward one time step
shift-j go backward several time steps
n go to now (the most recent data)
shift-c show the date selection calendar
i go up one pressure level
shift-i go up to the stratosphere
m go down one pressure level
shift-m go down to the surface
g toggle the grid on/off
p toggle the animation on/off
shift-h enable/disable high definition mode

translators

1599763839 1992pb 2451158917 afropolakwot agagey Aleksander Alexander Kirilov Alexey Dmitriev Alexey Korsakov AlexOrlovets Anderson Porto Andre Lz Andrea de Franco Andrew Pedrini Andrey Bagmanov Antonpek arquerogonza Artur Wisniewski ashawesoman ashvin.j.sherathiya astrostrong asveruz atom benji.poirier bgij bidulem3 Birg3r Bohuslav Šín Bram Versteeve Bryan carina.bringedal carlofrc Cassiel Bclamson Ching-ping Yu Christian Leroux contact cuxcoll Daniel Bartsch Daniel Isak Marinosson Daniel Pawlowski Daniel Rakoczy danielruiz1636 Darlite davalenciano98 Davide Carlier Denat250 deus.05 Dimitris T. Papadimitriou dlo.daniel Dominic Douglas dsantosgtm e Eason Huang egarpunov elier.pila Eric Kim essaii32 estefilippini fantasy_lcl farrasoctara Felipe Faria florian-lerch franci00 FranklinZhang Frederik T. de Ridder fthmiln georg.loesel gherlainfo giacomo.gerosa Gian Centeno giospud gonzalo.ag88 gporter.seadog graceang graham.rimmington grol2901 Hebel holgersson Hyung Wook Jung Ichiro Wang Ignacio Sanz iii1212 InfoSecOne Jae Soo Park Jiří Batelka Joanna Rinne Joao Correia jocelot Jomari Joseph Barrera Jonathan Yang Jose A. Frias Morales juanpaexpedite kai.s.mueller Karol Sapiński Kiyun Jeon kjetil.hoiby kty5663 ku5an2901 laurapaccini leandro1212 leticia.tahnee lretamal Luboš Motl m_strugale marcello.carreira marco.prosdocimo Mark markeletona Markus Schley Martine Bolzinger Matt Tang Mattia Raffa mavilesilva melfi Melissa Ortiz Massó Meow Wang mgb Michael Purer Michael Michel Rivero mikami_1966.1118 mikele.fit95 Miquel Bayo Moreno mir597 MirageF1AZ Miroslaw Lisiak Mohannad Alahmadi nando nunolava1998 Oğuzhan Arı Olivier OLS-RU P_A_N_D_A_M_A_N Paul Bachem Paweł Kowalczyk pdobrev Personim Intaned Philippe Jabet Plamen Dobrev ProffLex Rafael Nonato Bassora rajeshgodvani RaskiPL reyfran8 Riccardo Monfardini robertrosalex Roger Helman Roller978 rosariainpo Russel Schwartz santiago.giraldoc sapan021 sarogrom Seongmin Park september43 Seregalsv Serega silverhaze030 Simone Dragoni siudzin98 skyneon77 sombrasbaul Somil Thesia Stephen Flynn Steven Sunny Miu Tayseer M Alhibshi Telmo John tenderstart thanhhuyenlth Thomas Middelveld Thorsten Schleicher tigormal tigra200sx Tomasz Waligóra torstenleibrich ulaszewski.bartosz ultordima Vasily Tarasenko vhc1967 Víctor Velarde Vu Thuong wasted webfreelance Wonmin Jeong wtlovergirl xesmedic xorpid xrdeem xsqz yaawwad Yauhen Bahashou youngjune4498 Youngmin Jeon Yukun Chen zackcaussy Zulus Οverlord Александр Попов Вячеслав Епиков 피시 潘柏綸

Selected for inclusion in the Climate Literacy and Energy Awareness Network (CLEAN) collection of educational resources.

The GEOS-5 data used on this site have been provided by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center through the online data portal in the NASA Center for Climate Simulation

Generated using Copernicus Atmosphere Monitoring Service Information 2017-2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of this information.

Landschützer, Peter; Gruber, Nicolas; Bakker, Dorothee C. E. (2017). An observation-based global monthly gridded sea surface pCO2 product from 1982 onward and its monthly climatology (NCEI Accession 0160558). Version 4.4. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/V5Z899N6. [2019-03-27]

weather and ocean data are generated from numerical models

earth.nullschool.net implies no guarantee of accuracy

Copyright (c) 2019 Cameron Beccario