earth

uma visualização das condições de climaticas globais
boletins gerados por supercomputadores
atualizados a cada três horas

superfície estimatida do oceano
atualizadas a cada cinco dias

temperaturas de superfície do oceano e
anomalia da média diária (1981-2011)
atualizada diariamente

ondas do oceano
atualizadas a cada três horas

aurora
updated every thirty minutes

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)

A camada de "Superfície" representa as condições no terreno ou do nível da água
esta camada segue os contornos das montanhas, vales, 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

sobre ondas do oceano

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.

sobre concentrações de CO₂
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.

reclamação

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.

sobre aerossóis e extinção

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.

about active fire data

Fire data is a combination of VIIRS 375m NRT (NOAA-20) and VIIRS 375m NRT (Suomi NPP) active fire products. Each fire detection data point contains the time of detection (when the satellite made the measurement) and the Fire Radiative Power (FRP) in units of megawatts (MW). For more information on how to interpret the readings, see the FIRMS FAQ and the detailed discussion of VIIRS I-Band 375 m Active Fire Data.

We acknowledge the use of data and/or imagery from NASA's Fire Information for Resource Management System (FIRMS), part of NASA's Earth Observing System Data and Information System (EOSDIS).

atalhos do teclado

tradutores

Александр Попов Вячеслав Епиков 1599763839 1992pb 2451158917 피시 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 dustyhofman 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 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 m_strugale nando nunolava1998 Olivier OLS-RU Oğuzhan Arı Paul Bachem Paweł Kowalczyk pdobrev Personim Intaned Philippe Jabet Plamen Dobrev ProffLex P_A_N_D_A_M_A_N 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 SUGIMOTO Tatsuo Sunny Miu Tayseer M Alhibshi Telmo John tenderstart thanhhuyenlth Thomas Middelveld Thorsten Schleicher tigormal tigra200sx Tomasz Waligóra torstenleibrich tsuka tama ulaszewski.bartosz ultordima Vasily Tarasenko vhc1967 Vu Thuong Víctor Velarde wasted webfreelance Wonmin Jeong wtlovergirl xesmedic xorpid xrdeem xsqz 潘柏綸 yaawwad Yauhen Bahashou youngjune4498 Youngmin Jeon Yukun Chen zackcaussy Zulus Οverlord

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

Os dados usados no GEOS-5 foram fornecidos pelo escritório de assimilação (GMAO) na NASA Goddard Space Flight Center e modelagem Global através do portal de dados on-line no centro da NASA para a simulação de clima

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.