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Participantes Dr. Brian Mapes Dr. Kelly Chance Dr. David Raymond Dr. Miguel A. Rico Ramírez Dra. Carmen Galán Soldevilla Dr. Aaron Boone Dra. Ana P. Barros Dr. Dennis Hartmann |
TEMPO: Hourly satellite measurements of TEMPO will launch in 2019 to measure air pollution of North America, from Mexico City to the Canadian tar/oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution. TEMPO spectroscopic measurements in the ultraviolet and visible wavelengths will provide a tropospheric measurement suite that includes the key gases of tropospheric air pollution chemistry. Measurements are from geostationary orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. A small product spatial footprint resolves pollution sources at a sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a geostationary (GEO) host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and Ultraviolet B (UVB) radiation. TEMPO thus can measure the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, reducing uncertainty in air quality predictions by 50%. It provides near-real-time air quality products that will be made widely and publicly available. TEMPO makes the first tropospheric trace gas measurements from GEO, by building on the heritage of six spectrometers flown in low-earth-orbit (LEO). These LEO instruments measure the needed spectra, although at coarse spatial and temporal resolutions, to the precisions required for TEMPO and use retrieval algorithms developed for them by TEMPO Science Team members and currently running in operational environments. This measurement strategy makes TEMPO an innovative use of well-proven techniques, able to produce a revolutionary dataset. Kelly Chance
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