Coherent signature of warming-induced extreme sub-continental boreal wildfire activity 4800 and 1100 years BP
TL;DR: In this paper, the authors used anetwork of 42 lake-sediment charcoal records across a ∼2,000 km transect in easternborealNorth America to infer widespreadperiodsofwildfire activity in association with past climate conditions, finding past analogs for periodsof extreme biomass burning would provide valuable insights regardingwhat the effects of warming might be for tree species distribution, ecosystem integrity, atmospheric greenhouse gas balance, and human safety.
Abstract: Climate changes are expected toprogressively increase extremewildfire frequency in forests. Findingpast analogs for periodsof extremebiomass burningwouldprovide valuable insights regardingwhat the effects ofwarmingmight be for tree speciesdistribution, ecosystem integrity, atmospheric greenhouse gas balance, andhuman safety.Here,weused anetworkof 42 lake-sediment charcoal records across a∼2000 km transect in easternborealNorthAmerica to inferwidespreadperiodsofwildfire activity in associationwith past climate conditions.The reconstructedfluctuations inbiomassburning arebroadly consistentwith variations in ethane concentration inGreenlandpolar ice cores.Biomassburningfluctuations also significantly co-variedwithGreenland temperatures estimated from ice cores, at least for thepast 6000 years.Our retrospective analysis of pastfire activity allowedus to identify twofire periods centered around 4800 and1100BP, coincidingwith large-scalewarming innorthern latitudes andhaving respectively affected an estimated∼71%and∼57%of the study area.These twoperiods co-occurredwithwidespread decreases inmeanfire-return intervals.The twoperiods are likely thebest analogs forwhat couldbe anticipated in termsof impacts offireonecosystemservices providedby these forests in comingdecades.
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TL;DR: The 50th anniversary of the Canadian Journal of Forest Research (CJFR) was celebrated by reflecting on the considerable progress accomplished in select areas of Canadian wildland fire science over the past decade as mentioned in this paper.
Abstract: We celebrate the 50th anniversary of the Canadian Journal of Forest Research by reflecting on the considerable progress accomplished in select areas of Canadian wildland fire science over the past ...
32 citations
TL;DR: In this article, the authors analyzed fire weather and fire regimes in Central Asia from 2001-2015 and projected the impacts of climate change on fire weather in the 2030s (2021-2050) and 2080-2090 (2071-2099), which would help for improving wildfire management and adapting to future climate change in the region.
Abstract: This study analyzed fire weather and fire regimes in Central Asia from 2001–2015 and projected the impacts of climate change on fire weather in the 2030s (2021–2050) and 2080s (2071–2099), which would be helpful for improving wildfire management and adapting to future climate change in the region. The study area included five countries: Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan. The study area could be divided into four subregions based on vegetation type: shrub (R1), grassland (R2), mountain forest (R3), and rare vegetation area (R4). We used the modified Nesterov index (MNI) to indicate the fire weather of the region. The fire season for each vegetation zone was determined with the daily MNI and burned areas. We used the HadGEM2-ES global climate model with four scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) to project the future weather and fire weather of Central Asia. The results showed that the fire season for shrub areas (R1) was from 1 April to 30 November, for grassland (R2) was from 1 March to 30 November, and for mountain forest (R3) was from 1 April to 30 October. The daily burned areas of R1 and R2 mainly occurred in the period from June–August, while that of R3 mainly occurred in the April–June and August–October periods. Compared with the baseline (1971–2000), the mean daily maximum temperature and precipitation, in the fire seasons of study area, will increase by 14%–23% and 7%–15% in the 2030s, and 21%–37% and 11%–21% in the 2080s, respectively. The mean MNI will increase by 33%–68% in the 2030s and 63%–146% in the 2080s. The potential burned areas of will increase by 2%–8% in the 2030s and 3%–13% in the 2080s. Wildfire management needs to improve to adapt to increasing fire danger in the future.
19 citations
TL;DR: In this article , the historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability.
Abstract: Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire span-ning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America.
18 citations
16 Dec 2015
TL;DR: In this article, a series of transient Coupled General Circulation Model simulations was used to determine the past behavior of the El Niño Southern Oscillation (ENSO) over the past 21,000 years.
Abstract: The El Niño Southern Oscillation (ENSO) is Earth’s dominant source of interannual climate variability, but its response to global warming remains highly uncertain. To improve our understanding of ENSO’s sensitivity to external climate forcing, it is paramount to determine its past behaviour by using palaeoclimate data and model simulations. Palaeoclimate records show that ENSO has varied considerably since the Last Glacial Maximum (21,000 years ago), and some data sets suggest a gradual intensification of ENSO over the past ∼6,000 years. Previous attempts to simulate the transient evolution of ENSO have relied on simplified models or snapshot experiments. Here we analyse a series of transient Coupled General Circulation Model simulations forced by changes in greenhouse gasses, orbital forcing, the meltwater discharge and the ice-sheet history throughout the past 21,000 years. Consistent with most palaeo-ENSO reconstructions, our model simulates an orbitally induced strengthening of ENSO during the Holocene epoch, which is caused by increasing positive ocean–atmosphere feedbacks. During the early deglaciation, ENSO characteristics change drastically in response to meltwater discharges and the resulting changes in the Atlantic Meridional Overturning Circulation and equatorial annual cycle. Increasing deglacial atmospheric CO2 concentrations tend to weaken ENSO, whereas retreating glacial ice sheets intensify ENSO. The complex evolution of forcings and ENSO feedbacks and the uncertainties in the reconstruction further highlight the challenge and opportunity for constraining future ENSO responses.
10 citations
29 Sep 2020
TL;DR: In this paper, the authors developed a modelling framework that provides insights into processes and changes involved through time in the historical fire-vegetation-climate environment of the coniferous and mixedwood forests of eastern boreal North America, with a particular attention on the metric of fire size.
Abstract: Wildland fire is the most important disturbance in boreal forests of eastern North America, shaping composition, structure and spatial arrangement of the flora. Although the long-term evolution of frequency and quantity of biomass burnt in these forest are known relatively well from paleoecological studies, we know little about the evolution of fire sizes. Here, we developed a modelling framework that provides insights into processes and changes involved through time in the historical fire-vegetation-climate environment of the coniferous and mixedwood forests of eastern boreal North America, with a particular attention on the metric of fire size. On the one hand, lacustrine charcoal particles sequestered in sediments from mixedwood forest and coniferous forest regions (MF and CF, respectively) were analyzed with the most advanced statistical treatments to reconstruct changes in biomass burning, fire frequency, and their ratio, the fire size (FS index), over the last 7000 BP. On the other hand, a fire propagation model was used to simulate fire sizes in the past using both a reference landscape, whose MF and CF compositions through time were prescribed using pollen reconstructions, and climate inputs provided by the HadCM3BL-M1 snapshot simulations. Lacustrine charcoals showed that Holocene FS indices have not differed significantly between MF and CF due to high variability in fire frequencies. However, biomass burning from MF has always been lower than from CF, such differences being significant since 5000 BP. Beyond the variability, MF’s mean FS index was lower than CF’s one throughout the Holocene, with slight changes in both forests from 7000 to 1000 BP, and simultaneous increases over the last millennium. The fire model showed that MF fires were systematically smaller than CF ones throughout the Holocene, with larger differences in the past than today. The fire model also highlighted that spring fires in both forest types have always been larger than summer fires over the last 7000 years, such results being in agreement with present-day fire statistics. This study illustrates how fire models, built and used for forecast and firefighting today, can be used under past conditions to enhance our understanding in the fire-vegetation-climate nexus.
6 citations
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
Queen's University Belfast1, Collège de France2, English Heritage3, University of Arizona4, University of Sheffield5, University of Oxford6, University of Minnesota7, University of Hohenheim8, University of Kiel9, Lawrence Livermore National Laboratory10, University of Bergen11, ETH Zurich12, University of Waikato13, Woods Hole Oceanographic Institution14, Swiss Federal Institute for Forest, Snow and Landscape Research15, Cornell University16, University of Bristol17, University of Glasgow18, University of California, Irvine19, University of New South Wales20
TL;DR: In this paper, Heaton, AG Hogg, KA Hughen, KF Kaiser, B Kromer, SW Manning, RW Reimer, DA Richards, JR Southon, S Talamo, CSM Turney, J van der Plicht, CE Weyhenmeyer
Abstract: Additional co-authors: TJ Heaton, AG Hogg, KA Hughen, KF Kaiser, B Kromer, SW Manning, RW Reimer, DA Richards, JR Southon, S Talamo, CSM Turney, J van der Plicht, CE Weyhenmeyer
13,605 citations
Journal Article•
5,701 citations
TL;DR: It is demonstrated how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series and Monte Carlo methods are used to assess the statistical significance against red noise backgrounds.
Abstract: Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coher- ence for examining relationships in time frequency space be- tween two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (http://www.pol.ac.uk/home/research/waveletcoherence/). As we are interested in extracting low s/n ratio signals in time series we discuss only CWT in this paper. While CWT is a common tool for analyzing localized intermittent os- cillations in a time series, it is very often desirable to ex- amine two time series together that may be expected to be linked in some way. In particular, to examine whether re- gions in time frequency space with large common power have a consistent phase relationship and therefore are sug- gestive of causality between the time series. Many geophys- ical time series are not Normally distributed and we suggest methods of applying the CWT to such time series. From two CWTs we construct the Cross Wavelet Transform (XWT) which will expose their common power and relative phase in time-frequency space. We will further define a measure of Wavelet Coherence (WTC) between two CWT, which can find significant coherence even though the common power is low, and show how confidence levels against red noise back- grounds are calculated. We will present the basic CWT theory before we move on to XWT and WTC. New developments such as quanti- fying the phase relationship and calculating the WTC sig- nificance level will be treated more fully. When using the methods on time series it is important to have solid mecha- nistic foundations on which to base any relationships found, and we caution against using the methods in a "scatter-gun" approach (particularly if the time series probability density functions are modified). To illustrate how the various meth- ods are used we apply them to two data sets from meteo- rology and glaciology. Finally, we will provide links to a MatLab software package.
4,586 citations
"Coherent signature of warming-induc..." refers background or methods in this paper
...%) of the WTC against red noise backgrounds was estimated using Monte Carlo generated noise with 1000 surrogate data set pairs (having the same first-order autocorrelation coefficients as the input datasets; see Grinsted et al 2004)....
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...In-phase and antiphase relationshipsmay be interpreted respectively as positive and negative correlations in time and period (Grinsted et al 2004). temperature reconstruction and the p̂CHAR record indicated areas of significant and almost in-phase correlation at periodicities of>800 years per cycle…...
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...Relationships between variables under study were examined using non-parametric stationary bootstrapped correlations (Mudelsee 2003) and wavelet coherence (WTC) analyses (Grinsted et al 2004)....
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3,494 citations