earth

전세계 날씨상황
슈퍼컴퓨터 예보
3시간마다 업데이트

해류 예보
5일마다 업데이트

해수면 온도 및
일평균으로부터의 이상 (1981-2011)
매일 업데이트

바다의 파도는
3시간 마다 업데이트 됩니다

오로라는
매 30분마다 업데이트됩니다

대기압은 일반적으로 고도에 반비례합니다
몇몇 대기압의 경우 기상학적으로 특별한 의미를 지닙니다
지구가 매끄러운 구라 가정하고 계산합니다
참고: 1 헥토파스칼 (hPa) = 1 밀리바 (mb)

"표면"은 지면이나 수면을 말하며
이는 산이나 골짜기의 윤곽을 따라 정해집니다.

오버레이에서는 색상을 이용해 지도에 대략적인 값을 표시하며
특정 고도에서만 유효한 오버레이도 있고
그 외에는 어느 고도에서나 유효합니다

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.

CO₂ 농도
2017-01-24 04:30 UTC 이전 자료 열람 시 참고 사항

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.

2017-01-24 UTC부터는 GEOS-5가 업그레이드 되었으므로 더 이상 값을 조정할 필요가 없습니다.

면책 조항

화학물질 및 미세먼지 레이어 구현에 사용된 GEOS-5 데이터를 이용할 때 다음 면책 조항을 읽어보십시오: GEOS 시스템을 활용한 예측 데이터는 실험적이며 연구 목적으로만 생성되었습니다. 이러한 예측을 단순 조사 이외의 사안에서 이용하는 것은 권장하지 않습니다.

에어로졸과 소광 효과

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.

키보드 단축키

번역해주신 분들

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.

이 사이트에서 사용된 GEOS-5 데이터는 NASA 고다드 우주 비행 센터의 글로벌 모델링 및 동화 사무소(GMAO)에서 NASA 기후 시뮬레이션 센터의 온라인 데이터 포털을 통해 제공되었습니다

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]