Fires and Thick Smoke Across Southeast Asia: Image of the Day
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vehicles and power plants are not the only sources of air pollution and greenhouses gases: fires contribute, too. In the Northern Hemisphere spring, which is the end of dry season across much of Southeast Asia, thousands of fires burn each year as people clear cropland and pasture in anticipation of the upcoming wet (growing) season. Intentional fires also escape people's control and burn into adjacent forest. The smoke from these fires crosses the Pacific Ocean, affecting climate far away. This dramatic photo-like image of fires and smoke in Southeast Asia was captured on April 2, 2007, by the Moderate Resolution Imaging Spectroradiometer modis.gsfc.nasa.gov (MODIS) on NASA's aqua.nasa.gov Aqua satellite. MODIS detected hundreds, possibly thousands of fires (marked in red), burning in Thailand, Laos, Vietnam, and China. Thick smoke hides nearly all of Laos, where the highest concentration of fires is located. In southern China and northern Vietnam, the smoke has sunk into the valleys that crisscross the mountainous terrain; only the highest ridgelines, which appear dark green, emerge from the blanket of smoke. The smoke sails above a bank of clouds at upper right as a dingy, yellowish haze. Fires have been burning in the region for more than month, as shown by the high carbon monoxide levels observed by NASA's MOPITT sensor earthobservatory.nasa.gov/NaturalHazards/natural_hazards_v2.php3?img_id=14191 during March 2007. In addition to carbon dioxide and other greenhouse gases, fires produce tiny particles of incompletely burned, or charred, carbon. According to research published in mid-March 2007 in the Journal of Geophysical Research, significant amounts of this travel across the Pacific Ocean to North America at altitudes above 2 kilometers. In spring 2004, between 25-35 gigatons (roughly 55 to 77 million pounds) of black carbon crossed the Pacific and entered skies over western North America between March 26 and April 25; nearly 75 percent of it came from Asia. (Smoke and other pollution have no respect for borders; for example, scientists have also documented smoke pollution from fires in Alaska and Canada earthobservatory.nasa.gov/Study/ContributionPollution/ crossing the Atlantic and entering skies over Europe.) Black carbon influences the climate. Like any dark-colored material, it absorbs incoming sunlight, dimming and cooling the Earth's surface. But while the surface cools, the atmosphere where the black carbon is located heats up. Which effect is stronger? When scientists looked at the overall effect for an entire column of the atmosphere, black carbon's warming effects outweighed its cooling effects. They concluded that trans-Pacific transport of black carbon, such as the soot released from the fires shown in this image, may amplify greenhouse-gas warming over the western United States and the Pacific Ocean. The analysis was based on a variety of information, including weather models, observations collected from airplanes, and aerosol data from MODIS. The large image provided above has a spatial resolution (level of detail) of 250 meters per pixel. The MODIS Rapid Response Team provides rapidfire.sci.gsfc.nasa.gov/subsets/?FAS_China5 twice-daily images of the region in additional resolutions and formats. Hadley, O., Ramanathan, V., Carmichael, G., Tang, Y., Corrigan, C., Roberts, G., and Mauger, G. (2007). Trans-Pacific transport of black carbon and fine aerosols (D
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.046 | 0.001 |
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 it