A New Era of Air Quality Monitoring from Space overNorth America with TEMPO: Commissioning and Early Nominal Operation Results
Bibliographic record
Abstract
We present an overview of the initial data products of TEMPO during its commissioning and early nominal operation and preliminary comparison with correlative satellite and ground-based observations.TEMPO is NASA’s first Earth Venture Instrument (EVI) and first host payload. It measures hourly daytime atmospheric pollution over North America from Mexico City to the Canadian oil sands, and from the Atlantic to the Pacific, at high spatiotemporal resolution (~10 km2 at boresight) from the geostationary (GEO) orbit. It uses UV/visible spectroscopy (293-493 nm, 538-741 nm) to measure O3 profiles including lower tropospheric O3 and columns of NO2, H2CO, SO2, C2H2O2, H2O, BrO, IO, as well as clouds aerosols, and UVB. TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry and captures the inherent high variability in the diurnal cycle of emissions and chemistry. The TEMPO instrument was built by Ball in 2018. It was integrated into the host commercial communication satellite Intelsat 40e (IS-40e) by Maxar. IS-40e was successfully launched on April 7 by a SpaceX Falcon 9 rocket on to the GEO orbit at 91°W. The TEMPO Instrument powered up for the first time on orbit in early June to start its commissioning. After a month of dry out and activation, TEMPO first light of solar and earth measurements occurred on July 31-August 2. Nominal operation started on 19 October 2023 after the commissioning phase and the post-launch acceptance review. Science data products are archived and distributed at NASA’s ASDC and will be released to the public in approximately February 2024 for L1b and in April 2024 for L2/3. TEMPO is part of a geostationary constellation to measure air quality along with GEMS (launched in Feb. 2020) over Asia and Sentinel-4 (to launch in 2024) over Europe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".