The high resolution NEEM aerosol records over the last 3000 years: A new approach to determine wildfire frequency
Bibliographic record
Abstract
The importance of atmospheric aerosols and associated chemical processes as important drivers of climate change has been recognised, although their effect on the Earth’s radiative forcing is difficult to quantify and is therefore associated with large uncertainties. Episodic events, such as volcanic eruptions, emit considerable amounts of aerosols into the troposphere, or even into the lower stratosphere, where they disperse and can have an impact on climatic parameters, such as temperature and precipitation. Anomalies in climate parameters such as sea level pressure or surface temperatures can, have an influence on the manifestation of atmospheric patterns, which trigger extreme events. Teleconnection such as these modulate climate variability on different temporal and spatial scales. The occurrence of extensive wildfires on the North American continent, for example, has been associated with anomalies in the El Ni˜no Southern Oscillation/Pacific Decadal Oscillation (ENSO/PDO) and Arctic Oscillation (AO) patterns, causing drought conditions over extensive areas. In case of abundant fuel availability, areas of several 1000 km2 are then ignited. The fire plume containing a wealth of gaseous and particulate chemical species, which are subject to chemical reactions forming aerosols. These aerosols can, if the prevailing atmospheric conditions are favourable, i.e. if the wind tracks are directed accordingly and if rain does not scavenge the aerosols en route, be transported over large distances and thus reach Greenland, where they are eventually deposited and incorporated into the ice matrix. One example of a precursour gas emitted during biomass burning is ammonia NH3, one of the most abundant gaseous bases in the troposphere and thus highly important in the neutralisation of acidic aerosols. NH3 is rapidly transformed to ammonium NH+4 , which is incorporated into aerosols and can thus be transported to Greenland. NH3 is not only emitted during wildfires, but shows a distinctive cycle following biological activity peaking in late spring to early summer and remaining low during winter months. The Bern system for continuous flow analysis (CFA) was deployed in the camp of the North Greenland Eemian Ice Drilling (NEEM) project during the summers from 2009-2011 to analyse concentrations of aerosol constituents incorporated in the ice. Among other species, concentrations of NH+4 have been analysed. They show the distinct seasonal cycle with concentrations of 6 ppb in summer and 1 ppb in winter. However, from May through August of some years, concentrations are considerably higher, by up to 40 times compared to the natural background. These higher concentrations during the fire season are associated with biomass burning in northern North America and Canada. The NH+4 record from the Greenland ice sheet was therefore suggested to yield the biomass burning history of Canada. Additionally, the reconstruction of wildfire frequency yields information on past wildfire occurrence related to changes in climate. In order to examine the frequency of seasonal, episodic extreme events such as wildfires, a record of sub-seasonal resolution from a stratified and dated archive is necessary. Ice cores comply with the demands on the archive, and NH3 analysed with CFA complies with the demand on the resolution. The aim of this thesis was to establish a fire frequency over the late Holocene. For this purpose, the NH+4 data have been divided into a background trend and residuals, which also contain the extreme events using Singular Spectrum Analysis (SSA). Setting a running median threshold further distinguished the residuals from the extreme values. Correcting the extreme events for volcanic eruptions yields a biomass burning frequency over the last 3 kyr. However, due to the small number of events, the frequency is not representative. After testing the method on a published history of volcanic eruptions, we conclude, that the method to derive the frequency of extreme events is successful, but that only very few wildfire events are recorded in the Greenland ice.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".