scholarly journals Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Ke Shi ◽  
Yoshiya Touge
Keyword(s):  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Burned Area ◽  
North Pacific Oscillation ◽  
East Atlantic ◽  
Wildfire Management ◽  
East Pacific ◽  
Climatic Drivers ◽  
Homogeneous Regions

AbstractWildfires are widespread disasters and are concurrently influenced by global climatic drivers. Due to the widespread and far-reaching influence of climatic drivers, separate regional wildfires may have similar climatic cause mechanisms. Determining a suite of global climatic drivers that explain most of the variations in different homogeneous wildfire regions will be of great significance for wildfire management, wildfire prediction, and global wildfire climatology. Therefore, this study first identified spatiotemporally homogeneous regions of burned area worldwide during 2001–2019 using a distinct empirical orthogonal function. Eight patterns with different spatiotemporal characteristics were identified. Then, the relationships between major burned area patterns and sixteen global climatic drivers were quantified based on wavelet analysis. The most significant global climatic drivers that strongly impacted each of the eight major wildfire patterns were identified. The most significant combinations of hotspots and climatic drivers were Atlantic multidecadal Oscillation-East Pacific/North Pacific Oscillation (EP/NP)-Pacific North American Pattern (PNA) with the pattern around Ukraine and Kazakhstan, El Niño/Southern Oscillation-Arctic Oscillation (AO)-East Atlantic/Western Russia Pattern (EA/WR) with the pattern in Australia, and PNA-AO-Polar/Eurasia Pattern-EA/WR with the pattern in Brazil. Overall, these results provide a reference for predicting wildfire and understanding wildfire homogeneity.

Influence of Atmospheric Teleconnections on Interannual Variability of Boreal Fires

2020 ◽  
Author(s):  
Zhiyi Zhao ◽  
Zhongda Lin ◽  
Fang Li
Keyword(s):  
Interannual Variability ◽  
Large Scale ◽  
Driving Forces ◽  
Southern Oscillation ◽  
Burned Area ◽  
East Atlantic ◽  
Local Climate ◽  
Atmospheric Teleconnection ◽  
Teleconnection Patterns ◽  
Global Carbon

<p>Wildfires are common in boreal forests around the world and strongly affect regional ecosystem processes and global carbon cycle. Previous studies have suggested that local climate is a dominant driver of boreal fires. However, the impacts of large-scale atmospheric teleconnection patterns on boreal fires and related physical processes remain largely unclear. This study investigates the influence of nine leading atmospheric teleconnection modes and El Niño-Southern Oscillation (ENSO) on the interannual variability of simultaneous summer fires in the boreal regions based on 1997-2015 GFED4s burned area, NCEP/NCAR atmospheric reanalysis, and HadISST sea surface temperature. Results show that ENSO has only a weak effect on boreal fires, distinct from its robust influence on the tropical fires. Instead, the interannual variability of burned area in the boreal regions is significantly regulated by five teleconnection patterns. Specifically, East Pacific-North Pacific (EP/NP) and East Atlantic/West Russia (EA/WR) patterns affect the burned area in North America, North Atlantic Oscillation (NAO) and East Atlantic (EA) patterns for Asia, and the Pacific-North American (PNA) pattern for Europe. Related to the teleconnections, the larger burned area is attributable to warmer surface by an anomalous high-pressure above and drier surface due to less moisture transport from the neighboring oceans. The results improve our understanding of driving forces of interannual variability of boreal fires and then regional and global carbon budgets.</p>

scholarly journals Evaluating Spatiotemporal Patterns and Trends of Drought in Japan Associated with Global Climatic Drivers

2021 ◽  
Author(s):  
Ke Shi ◽  
Yoshiya Touge ◽  
So Kazama
Keyword(s):  
Wavelet Transform ◽  
Potential Evapotranspiration ◽  
Kendall Test ◽  
Severity Index ◽  
Wavelet Coherence ◽  
Burned Area ◽  
Drought Severity ◽  
Arctic Oscillation Index ◽  
Climatic Drivers ◽  
Homogeneous Regions

Abstract. Drought disasters, such as water scarcity and wildfires, are serious natural disasters in Japan that are also affected by climate change. However, as drought generally has widespread impacts and the duration of drought can vary considerably, it is difficult to assess the spatiotemporal characteristics and the climatic causes of drought. Therefore, to identify the drought homogeneous regions and understand climatic causes of regional drought over Japan, this study provides a spatiotemporal analysis for historical droughts patterns and teleconnections associated with global climatic drivers. The trends of meteorological elements, which are the basis of drought index calculation, was first assessed. Then, drought characterized by the Self-calibrating Palmer Drought Severity Index (scPDSI) was investigated. Trends and patterns of drought were identified through the trend-free pre-whitening Mann-Kendall test and distinct empirical orthogonal function. The continuous wavelet transform and cross wavelet transform together with wavelet coherence were utilized to depict the links between drought and global climatic drivers. The results are described as follows: (1) the trends of precipitation were insignificant. However, temperature and potential evapotranspiration increasing trends were detected over Japan; (2) the drought trend over Japan varied seasonally, increasing in spring and summer and decreasing in autumn and winter; (3) two major subregions of drought variability—the western Japan (W region) and most of the northernmost Japan near the Pacific (N region) were identified; (4) wildfires with large burned area were more likely to occur when the scPDSI was less than −1; and (5) the North Atlantic Index (NAOI) showed the strongest coherence connections with Distinguished Principle Components-1 among four climatic drivers. Additionally, Distinguished Principle Components-2 showed stronger coherence connections with NAOI and Arctic Oscillation Index. This study is the first to identify homogeneous regions with distinct drought characteristics over Japan and connect the drought in Japan with the global climatic drivers.

Regional relationships between climate and wildfire-burned area in the Interior West, USA

2006 ◽  
Vol 36 (3) ◽  
pp. 699-709 ◽  
Author(s):  
Brandon M Collins ◽  
Philip N Omi ◽  
Phillip L Chapman
Keyword(s):  
Southern Oscillation ◽  
Severity Index ◽  
Atlantic Multidecadal Oscillation ◽  
Burned Area ◽  
Drought Severity ◽  
Western Slope ◽  
The Pacific ◽  
Fuel Dynamics ◽  
Colorado Rockies ◽  
Interior West

Recent studies have linked the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) with drought occurrence in the interior United States. This study evaluates the influence of AMO and PDO phases on interannual relationships between climate and wildfire-burned area during the 20th century. Palmer's Drought Severity Index (PDSI) is strongly related to burned area at both regional and subregional scales. In the southern Interior West, PDSI is most strongly related to yearly burned area during warm-phase AMO, while for the same period no significant relationships exist between PDSI and burned area in the central Interior West. During cool-phase PDO, interannual climate has little influence on burned area in either the northern or the central Interior West. The opposite is true for the southern Interior West and the eastern slope of the Colorado Rockies using the Southern Oscillation Index and PDSI, respectively. The western slope of the Colorado Rockies is the only climate division or region in which burned area is not related to preceding PDSI. During warm-phase PDO, current PDSI explains 67% of the interannual variance in burned area on the western slope. These regional and temporal differences are most likely governed by variations in fuel dynamics associated with dominant regional and subregional vegetation types.

scholarly journals Effects of Climatic Drivers and Teleconnections on Late 20th Century Trends in Spring Freshet of Four Major Arctic-Draining Rivers

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 179
Author(s):  
Roxanne Ahmed ◽  
Terry Prowse ◽  
Yonas Dibike ◽  
Barrie Bonsal
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rate Of Change ◽  
The Arctic ◽  
Late 20Th Century ◽  
Basin Scale ◽  
The Arctic Ocean ◽  
Spring Freshet ◽  
Climatic Drivers

Spring freshet is the dominant annual discharge event in all major Arctic draining rivers with large contributions to freshwater inflow to the Arctic Ocean. Research has shown that the total freshwater influx to the Arctic Ocean has been increasing, while at the same time, the rate of change in the Arctic climate is significantly higher than in other parts of the globe. This study assesses the large-scale atmospheric and surface climatic conditions affecting the magnitude, timing and regional variability of the spring freshets by analyzing historic daily discharges from sub-basins within the four largest Arctic-draining watersheds (Mackenzie, Ob, Lena and Yenisei). Results reveal that climatic variations closely match the observed regional trends of increasing cold-season flows and earlier freshets. Flow regulation appears to suppress the effects of climatic drivers on freshet volume but does not have a significant impact on peak freshet magnitude or timing measures. Spring freshet characteristics are also influenced by El Niño-Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation and the North Atlantic Oscillation, particularly in their positive phases. The majority of significant relationships are found in unregulated stations. This study provides a key insight into the climatic drivers of observed trends in freshet characteristics, whilst clarifying the effects of regulation versus climate at the sub-basin scale.

scholarly journals The Life and Death of the Recent Global Surface Warming Hiatus Parsimoniously Explained

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 64 ◽  
Author(s):  
Kristoffer Rypdal
Keyword(s):  
Southern Oscillation ◽  
Thermal Inertia ◽  
Volcanic Eruptions ◽  
Atlantic Multidecadal Oscillation ◽  
Delayed Response ◽  
Small Contribution ◽  
Surface Warming ◽  
Life And Death ◽  
Model Driven ◽  
Warming Hiatus

The main features of the instrumental global mean surface temperature (GMST) are reasonably well described by a simple linear response model driven by anthropogenic, volcanic and solar forcing. This model acts as a linear long-memory filter of the forcing signal. The physical interpretation of this filtering is the delayed response due to the thermal inertia of the ocean. This description is considerably more accurate if El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are regarded as additional forcings of the global temperature and hence subject to the same filtering as the other forcing components. By considering these as predictors in a linear regression scheme, more than 92% of the variance in the instrumental GMST over the period 1870–2017 is explained by this model, in particular, all features of the 1998–2015 hiatus, including its death. While the more prominent pauses during 1870–1915 and 1940–1970 can be attributed to clustering in time of strong volcanic eruptions, the recent hiatus is an unremarkable phenomenon that is attributed to ENSO with a small contribution from solar activity.

Predicting wildfire vulnerability using logistic regression and artificial neural networks: a case study in Brazil's Federal District

2019 ◽  
Vol 28 (1) ◽  
pp. 35 ◽  
Author(s):  
Pablo Pozzobon de Bem ◽  
Osmar Abílio de Carvalho Júnior ◽  
Eraldo Aparecido Trondoli Matricardi ◽  
Renato Fontes Guimarães ◽  
Roberto Arnaldo Trancoso Gomes
Keyword(s):  
Logistic Regression ◽  
Characteristic Curve ◽  
Federal District ◽  
Burned Area ◽  
Ann Model ◽  
Wildfire Management ◽  
Explanatory Variables ◽  
Burned Areas ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Predicting the spatial distribution of wildfires is an important step towards proper wildfire management. In this work, we applied two data-mining models commonly used to predict fire occurrence – logistic regression (LR) and an artificial neural network (ANN) – to Brazil’s Federal District, located inside the Brazilian Cerrado. We used Landsat-based burned area products to generate the dependent variable, and nine different anthropogenic and environmental factors as explanatory variables. The models were optimised via feature selection for best area under receiver operating characteristic curve (AUC) and then validated with real burn area data. The models had similar performance, but the ANN model showed better AUC (0.77) and accuracy values when evaluating exclusively non-burned areas (73.39%), whereas it had worse accuracy overall (66.55%) when classifying burned areas, in which LR performed better (65.24%). Moreover, we compared the contribution of each variable to the models, adding some insight into the main causes of wildfires in the region. The main driving aspects of the burned area distribution were land-use type and elevation. The results showed good performance for both models tested. These studies are still scarce despite the importance of the Brazilian savanna.

Hotspots of extreme compound drought and heatwaves: Role of feedback and climate oscillations

2021 ◽  
Author(s):  
Waqar Ul Hassan ◽  
Munir Ahmad Nayak
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Limited Attention ◽  
Weather Events ◽  
Excess Heat Factor ◽  
Climatic Drivers ◽  
Compound Events ◽  
Positive And Negative Feedbacks

<p>Compound weather events arise from combination of multiple climatic drivers or hazards and often result in disastrous socio-economic impacts. Compound drought and heatwave (CDHE) events have received considerable attention in recent years, but limited attention is given towards the understanding of feedback relationships between droughts and heatwaves at global hotspots of the compound events. Here, we identify the potential hotspots of extreme compound drought and heatwaves (ECDH) over the globe using standardized precipitation index (SPI) and Excess heat factor (EHF) as metrics for droughts and heatwaves, respectively. Besides the well know positive feedback between droughts and heatwaves, i.e., heatwaves amplify droughts and vice-versa, we hypothesize and test the possibility of negative feedback at distinct hotspots where heatwaves tend to abate droughts. Multiple hotspots were identified with positive and negative feedbacks among drought and heatwave intensities, supporting our hypothesis. We also analyzed the role of different local and large-scale global drivers (such as El-Niño Southern Oscillation) on the feedbacks at the hotspots. Our analysis has implications in predicting extreme compound droughts and heatwaves and provides new insights that will foster further research in this direction.</p>

On the influence of ENSO complexity on Pan-Pacific coastal wave extremes

2021 ◽  
Vol 118 (47) ◽  
pp. e2115599118
Author(s):  
Julien Boucharel ◽  
Rafael Almar ◽  
Elodie Kestenare ◽  
Fei-Fei Jin
Keyword(s):  
Southern Oscillation ◽  
Wave Activity ◽  
Spatial Behavior ◽  
Coastal Hazards ◽  
Climate Control ◽  
Enso Events ◽  
The Pacific ◽  
Coastal Impacts ◽  
Climate Mode

Wind-generated waves are dominant drivers of coastal dynamics and vulnerability, which have considerable impacts on littoral ecosystems and socioeconomic activities. It is therefore paramount to improve coastal hazards predictions through the better understanding of connections between wave activity and climate variability. In the Pacific, the dominant climate mode is El Niño Southern Oscillation (ENSO), which has known a renaissance of scientific interest leading to great theoretical advances in the past decade. Yet studies on ENSO’s coastal impacts still rely on the oversimplified picture of the canonical dipole across the Pacific. Here, we consider the full ENSO variety to delineate its essential teleconnection pathways to tropical and extratropical storminess. These robust seasonally modulated relationships allow us to develop a mathematical model of coastal wave modulation essentially driven by ENSO’s complex temporal and spatial behavior. Accounting for this nonlinear climate control on Pan-Pacific wave activity leads to a much better characterization of waves’ seasonal to interannual variability (+25% in explained variance) and intensity of extremes (+60% for strong ENSO events), therefore paving the way for significantly more accurate forecasts than formerly possible with the previous baseline understanding of ENSO’s influence on coastal hazards.

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