Tropospheric emissions: monitoring of pollution (TEMPO)

Chance, K.; Liu, Xueliang; Suleiman, R. M.; Flittner, D. E.; Al-Saadi, J. A.; Janz, S. J.

doi:10.1117/12.2024479

Cited by 82 publications

(76 citation statements)

References 53 publications

(62 reference statements)

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“…Figure 2 shows the spatial extent of the planned (pre-2020 launch) constellation of Earth observing geostationary (GEO) sensors TEMPO (Chance et al, 2013), Sentinel-4 (Ahlers et al, 2011), and GEMS (Kim, 2012). Coverage is largely limited to the northern hemisphere.…”

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

“…GEO satellites are positioned ~36 000 km above the Earth's equator and the planned instruments will observe the same point every hour at higher resolution than the deployed LEO satellites. The ground footprint of TEMPO, for example, is 2 km × 5 km at the center of the North American domain (Chance et al, 2013).…”

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

“…Skills scarcity on the continent can be addressed by training scientists at overseas institutions that specialize in retrieval and interpretation of remote sensing data. Instrument design and build can be outsourced to a private company, as is the case with TEMPO and GEMS (Chance et al, 2013).…”

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

“…Information gained from a GEO satellite will better constrain air quality models that are being developed at increasingly fine resolution. Current LEO sensors have limited sensitivity to surface O 3 (Zhang et al, 2010) that will be addressed with TEMPO by extending the spectrum to include the visible Chappuis O 3 band (Chance et al, 2013).…”

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

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A Geostationary Air Quality Monitoring Platform for Africa

Marais

Chance

2015

Clean Air J.

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African populations and economies are growing rapidly, but there are few surface observations to monitor the effects on air quality. Trend analysis of the 19-year record of space-based observations from remote sensors onboard low Earth orbit (LEO) satellites shows that anthropogenic pollution is on the rise. Conversely, biomass burning, the largest contributor to surface ozone, is declining. UVvisible instruments on LEO satellites with daily resolution have provided invaluable constraints on sources, evolution, and transport of air pollution in Africa. Sensors in geostationary orbit (GEO) with hourly resolution and a smaller ground pixel than current and past fleets of LEO satellites would further our understanding of air quality in Africa and address the dearth of surface monitoring sites on the continent. Africa has successfully launched Earth observation platforms to retrieve satellite imagery and should expand its remote sensing capabilities by joining the northern hemisphere constellation of GEO Earth observation satellites.

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Section: An African Geostationary Observation Platformmentioning

confidence: 99%

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

Section: An African Geostationary Observation Platformmentioning

confidence: 99%

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A Geostationary Air Quality Monitoring Platform for Africa

Marais

Chance

2015

Clean Air J.

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“…This will consist of the European Space Agency (ESA) Sentinel 4 over Europe (Ingmann et al, 2012), the Korean Aerospace Research Institute (KARI) GEMS satellite over Asia (http://eng.kari. re.kr/sub01_01_02_09), and the National Aeronautics and Space Administration (NASA) TEMPO mission over Amer- (Chance et al, 2013). These missions will provide unprecedented high-resolution measurement of air pollution with hourly observations from space (e.g., Fishman, 2008).…”

Section: Satellite Observationsmentioning

confidence: 99%

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

et al. 2015

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Abstract. Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models

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Satellite observations of CO₂ from a highly elliptical orbit for studies of the Arctic and boreal carbon cycle

et al. 2014

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Here we report on an observing system simulation experiment (OSSE) to compare the efficacy of near-infrared satellite observations of CO 2 from a highly elliptical orbit (HEO) and a low Earth orbit (LEO), for constraining Arctic and boreal CO 2 sources and sinks. The carbon cycle at these latitudes (~50-90°N) is primarily driven by the boreal forests, but increasing anthropogenic activity and the effects of climate change such as thawing of permafrost throughout this region could also have an important role in the coming years. A HEO enables quasi-geostationary observations of Earth's northern high latitudes, which are not observed from a geostationary orbit. The orbit and observing characteristics for the HEO mission are based on the Weather, Climate and Air quality (WCA) concept proposed for the Polar Communications and Weather (PCW) mission, while those for the LEO mission are based on the Greenhouse gases Observing Satellite (GOSAT). Two WCA instrument configurations were investigated. Adopting the Optimal configuration yielded an observation data set that gave annual Arctic and boreal regional terrestrial biospheric CO 2 flux uncertainties an average of 30% lower than those from GOSAT, while a smaller instrument configuration resulted in uncertainties averaging 20% lower than those from GOSAT. For either WCA instrument configuration, much greater reductions in uncertainty occur for spring, summer, and autumn than for winter, with Optimal flux uncertainties for June-August nearly 50% lower than from GOSAT. These findings demonstrate that CO 2 observations from HEO offer significant advantages over LEO for constraining CO 2 fluxes from the Arctic and boreal regions.

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Tropospheric emissions: monitoring of pollution (TEMPO)

Cited by 82 publications

References 53 publications

A Geostationary Air Quality Monitoring Platform for Africa

A Geostationary Air Quality Monitoring Platform for Africa

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

Satellite observations of CO₂ from a highly elliptical orbit for studies of the Arctic and boreal carbon cycle

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Tropospheric emissions: monitoring of pollution (TEMPO)

Cited by 82 publications

References 53 publications

A Geostationary Air Quality Monitoring Platform for Africa

A Geostationary Air Quality Monitoring Platform for Africa

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

Satellite observations of CO2 from a highly elliptical orbit for studies of the Arctic and boreal carbon cycle

Contact Info

Product

Resources

About

Satellite observations of CO₂ from a highly elliptical orbit for studies of the Arctic and boreal carbon cycle