scholarly journals Predicting Fire Season Intensity in Maritime Southeast Asia with Interpretable Models

2021 ◽  
Author(s):  
William Daniels ◽  
Dorit Hammerling ◽  
Rebecca Buchholz ◽  
Helen Worden ◽  
Fatimah Ahamad
Keyword(s):  
Climate Variability ◽  
Southeast Asia ◽  
Southern Oscillation ◽  
Longwave Radiation ◽  
Fire Season ◽  
Fire Intensity ◽  
Climate Index ◽  
Burned Area ◽  
Lead Times ◽  
Modeling Framework

There have been many extreme fire seasons in Maritime Southeast Asia (MSEA) over the last two decades, a trend which will likely continue, if not accelerate, due to climate change. Fires, in turn, are a major driver of atmospheric carbon monoxide (CO) variability, especially in the Southern Hemisphere. Previous studies have explored the relationship between climate variability and fire counts, burned area, and atmospheric CO through regression models that use climate mode indices as predictor variables. Here we model the connections between climate variability and atmospheric CO at a level of complexity not yet studied and make accurate predictions of atmospheric CO (a proxy for fire intensity) at useful lead times. To do this, we develop a regularization-based statistical modeling framework that can accommodate multiple lags of a single climate index, which we show to be an important feature in explaining CO. We use this framework to present advancements over previous modeling efforts, such as the inclusion of outgoing longwave radiation (OLR) anomalies, the use of high resolution weekly data, and a stability analysis that adds weight to the scientific interpretation of selected model terms. We find that the El Nino Southern Oscillation (ENSO), the Dipole Mode Index (DMI), and OLR (as a proxy for the Madden-Julian Oscillation) at various lead times are the most significant predictors of atmospheric CO in MSEA. We further show that the model gives accurate predictions of atmospheric CO at leads times of up to 6 months, making it a useful tool for fire season preparedness.

scholarly journals Precipitation–fire linkages in Indonesia (1997–2015)

2017 ◽  
Vol 14 (18) ◽  
pp. 3995-4008 ◽  
Author(s):  
Thierry Fanin ◽  
Guido R. van der Werf
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Fire Season ◽  
Coefficient Of Determination ◽  
Fire Intensity ◽  
Rainfall Time Series ◽  
Fire Emissions ◽  
Active Fire

Abstract. Over the past decades, fires have burned annually in Indonesia, yet the strength of the fire season is for a large part modulated by the El Niño Southern Oscillation (ENSO). The two most recent very strong El Niño years were 2015 and 1997. Both years involved high incidences of fire in Indonesia. At present, there is no consistent satellite data stream spanning the full 19-year record, thereby complicating a comparison between these two fire seasons. We have investigated how various fire and precipitation datasets can be merged to better compare the fire dynamics in 1997 and 2015 as well as in intermediary years. We combined nighttime active fire detections from the Along Track Scanning Radiometer (ATSR) World Fire Atlas (WFA) available from 1997 until 2012 and the nighttime subset of the Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor from 2001 until now. For the overlapping period, MODIS detected about 4 times more fires than ATSR, but this ratio varied spatially. Although the reasons behind this spatial variability remain unclear, the coefficient of determination for the overlapping period was high (R2 = 0. 97, based on monthly data) and allowed for a consistent time series. We then constructed a rainfall time series based on the Global Precipitation Climatology Project (GPCP, 1997–2015) and the Tropical Rainfall Measurement Mission Project (TRMM, 1998–2015). Relations between antecedent rainfall and fire activity were not uniform in Indonesia. In southern Sumatra and Kalimantan, we found that 120 days of rainfall accumulation had the highest coefficient of determination with annual fire intensity. In northern Sumatra, this period was only 30 days. Thresholds of 200 and 305 mm average rainfall accumulation before each active fire were identified to generate a high-incidence fire year in southern Sumatra and southern Kalimantan, respectively. The number of active fires detected in 1997 was 2.2 times higher than in 2015. Assuming the ratio between nighttime and total active fires did not change, the 1997 season was thus about twice as severe as the one in 2015. Although large, the difference is smaller than found in fire emission estimates from the Global Fire Emissions Database (GFED). Besides different rainfall amounts and patterns, the two-fold difference between 1997 and 2015 may be attributed to a weaker El Niño and neutral Indian Ocean Dipole (IOD) conditions in the later year. The fraction of fires burning in peatlands was higher in 2015 compared to 1997 (61 and 45 %, respectively). Finally, we found that the non-linearity between rainfall and fire in Indonesia stems from longer periods without rain in extremely dry years.

Florida wildfire activity and atmospheric teleconnections

2009 ◽  
Vol 18 (4) ◽  
pp. 476 ◽  
Author(s):  
Scott L. Goodrick ◽  
Deborah E. Hanley
Keyword(s):  
North American ◽  
Southern Oscillation ◽  
Fire Severity ◽  
Fire Season ◽  
Climate Index ◽  
Atmospheric Teleconnection ◽  
Pacific North American ◽  
Teleconnection Patterns ◽  
Area Burned ◽  
The North

Since 1991, the Florida Division of Forestry has been making seasonal fire severity forecasts based on a relationship between area burned in Florida and El Niño–Southern Oscillation (ENSO). The present study extends the original analysis on which these forecasts are based and attempts to augment it with the addition of other patterns of climate variability. Two atmospheric teleconnection patterns, the North Atlantic Oscillation and Pacific–North American pattern, are examined as potential indicators of seasonal and monthly area burned in Florida. Although ENSO was the only climate index to show a significant correlation to area burned in Florida, the Pacific–North American pattern (PNA) is shown to be a factor influencing fire season severity although the relationship is not monotonic and therefore not revealed by correlation analysis.

scholarly journals Prescribed Burning Reduces Large, High-Intensity Wildfires and Emissions in the Brazilian Savanna

Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 56
Author(s):  
Filippe L.M. Santos ◽  
Joana Nogueira ◽  
Rodrigo A. F. de Souza ◽  
Rodrigo M. Falleiro ◽  
Isabel B. Schmidt ◽  
...  
Keyword(s):  
High Intensity ◽  
Prescribed Burning ◽  
Fire Management ◽  
Fire Regime ◽  
Scientific Evidence ◽  
Brazilian Savanna ◽  
Fire Season ◽  
Fire Intensity ◽  
Burned Area ◽  
Fire Policy

Brazil has recently (2014) changed from a zero-fire policy to an Integrated Fire Management (IFM) program with the active use of prescribed burning (PB) in federal Protected Areas (PA) and Indigenous Territories (IT) of the Brazilian savanna (Cerrado). PB is commonly applied in the management of fire-prone ecosystems to mitigate large, high-intensity wildfires, the associated emissions, and high fire suppression costs. However, the effectiveness of such fire management in reducing large wildfires and emissions over Brazil remains mostly unevaluated. Here, we aim to fill the gap in the scientific evidence of the PB benefits by relying on the most up-to-date, satellite-derived fire datasets of burned area (BA), fire size, duration, emissions, and intensity from 2003 to 2018. We focused on two Cerrado ITs with different sizes and hydrological regimes, Xerente and Araguaia, where IFM has been in place since 2015. To understand fire regime dynamics, we divided the study period into three phases according to the prevalent fire policy and the individual fire scars into four size classes. We considered two fire seasons: management fire season (MFS, which goes from rainy to mid-dry season, when PBs are undertaken) and wildfires season (WFS, when PBs are not performed and fires tend to grow out of control). Our results show that the implementation of the IFM program was responsible for a decrease of the areas affected by high fire recurrence in Xerente and Araguaia, when compared with the Zero Fire Phase (2008–2013). In both regions, PB effectively reduced the large wildfires occurrence, the number of medium and large scars, fire intensity, and emissions, changing the prevalent fire season from the WFS to the MFS. Such reductions are significant since WFS causes higher negative impacts on biodiversity conservation and higher greenhouse gas emissions. We conclude that the effect on wildfires can still be reduced if effective fire management policies, including PB, continue to be implemented during the coming decades.

scholarly journals Varying relationships between fire radiative power and fire size at a global scale

2019 ◽  
Vol 16 (2) ◽  
pp. 275-288 ◽  
Author(s):  
Pierre Laurent ◽  
Florent Mouillot ◽  
Maria Vanesa Moreno ◽  
Chao Yue ◽  
Philippe Ciais
Keyword(s):  
Patch Size ◽  
Empirical Relation ◽  
Global Scale ◽  
Fire Season ◽  
Fire Intensity ◽  
Burned Area ◽  
Fire Size ◽  
Fire Emissions ◽  
Radiative Power ◽  
Fire Radiative Power

Abstract. Vegetation fires are an important process in the Earth system. Fire intensity locally impacts fuel consumption, damage to the vegetation, chemical composition of fire emissions and also how fires spread across landscapes. It has been observed that fire occurrence, defined as the frequency of active fires detected by the MODIS sensor, is related to intensity with a hump-shaped empirical relation, meaning that occurrence reaches a maximum at intermediate fire intensity. Raw burned area products obtained from remote sensing can not discriminate between ignition and propagation processes. To go beyond burned area and to test if fire size is driven by fire intensity at a global scale as expected from empirical fire spread models, we used the newly delivered global FRY database, which provides fire patch functional traits based on satellite observation, including fire patch size, and the fire radiative power measures from the MCD14ML dataset. This paper describes the varying relationships between fire size and fire radiative power across biomes at a global scale. We show that in most fire regions of the world defined by the GFED database, the linear relationship between fire radiative power and fire patch size saturates for a threshold of intermediate-intensity fires. The value of this threshold differs from one region to another and depends on vegetation type. In the most fire-prone savanna regions, once this threshold is reached, fire size decreases for the most intense fires, which mostly happen in the late fire season. According to the percolation theory, we suggest that the decrease in fire size for more intense late season fires is a consequence of the increasing fragmentation of fuel continuity throughout the fire season and suggest that landscape-scale feedbacks should be developed in global fire modules.

scholarly journals Assessing Wildfire Exposure to Communities and Protected Areas in Portugal

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 82
Author(s):  
Fermin Alcasena ◽  
Alan Ager ◽  
Yannick Le Page ◽  
Paulo Bessa ◽  
Carlos Loureiro ◽  
...  
Keyword(s):  
National Level ◽  
Landscape Management ◽  
Weather Data ◽  
Fire Season ◽  
Fire Intensity ◽  
Burned Area ◽  
Natural Areas ◽  
Pixel Resolution ◽  
Burn Probability ◽  
Wildfire Simulation

During the 2017 wildfire season in Portugal, unprecedented episodes burned 6% of the country’s area and underscored the need for a long-term comprehensive solution to mitigate future wildfire disasters. In this study, we built and calibrated a national-scale fire simulation system including the underlying fuels and weather data and used the system to quantify wildfire exposure to communities and natural areas. We simulated 10,000 fire season replicates under extreme weather to generate 1.6 million large wildfire perimeters and estimate annual burn probability and fire intensity at 100 m pixel resolution. These outputs were used to estimate wildfire exposure to buildings and natural areas. The results showed a fire exposure of 10,394 structures per year and that 30% of communities accounted for 82% of the total. The predicted burned area in natural sites was 18,257 ha yr−1, of which 9.8% was protected land where fuel management is not permitted. The main burn probability hotspots were in central and northern regions. We highlighted vital priorities to safeguard the most vulnerable communities and promote landscape management programs at the national level. The results can be useful to inform Portugal’s new national plan under implementation, where decision-making is based on a probabilistic methodology. The core strategies include protecting people and infrastructure and wildfire management. Finally, we discuss the next steps necessary to improve and operationalize the framework developed here. The wildfire simulation modeling approach presented in this study is extensible to other fire-prone Mediterranean regions where predicting catastrophic fires can help anticipate future disasters.

scholarly journals Varying relationships between fire intensity and fire size at global scale

2018 ◽  
Author(s):  
Pierre Laurent ◽  
Florent Mouillot ◽  
Maria Vanesa Moreno ◽  
Chao Yue ◽  
Philippe Ciais
Keyword(s):  
Patch Size ◽  
Empirical Relation ◽  
Satellite Observation ◽  
Fire Spread ◽  
Global Scale ◽  
Fire Season ◽  
Fire Intensity ◽  
Burned Area ◽  
Fire Size ◽  
Fire Emissions

Abstract. Vegetation fires are an important process in the Earth system. Fire intensity locally impacts fuel consumption, damage to the vegetation, chemical composition of fire emissions but also how fires spread across landscapes. It has been observed that fire occurrence, defined as the frequency of active fires detected by the MODIS sensor, is related to intensity with a hump-shaped empirical relation meaning that occurrence reaches a maximum at intermediate intensity. Raw burned area products obtained from remote-sensing can not discriminate between ignition and propagation processes. Here we use the newly delivered global FRY database, which provides fire patch functional traits including fire patch size from satellite observation, to go beyond burned area, and to test if fire size is driven by fire intensity at global scale as expected from empirical fire spread models. We show that in most regions of the world the linear relationship between fire intensity and fire patch size saturates for a threshold of intermediate intensity fires. The value of the threshold differs from one region to another, and we suggest that it might be driven by drought, and the amount of available biomass. In some regions, once this threshold is reached, we also observe that fire size decreases for the most intense fires, which mostly happen in the late fire season. According to the percolation theory, we suggest that this effect is a consequence of the increasing fragmentation of fuel continuity along the fire season so that landscape-scale feedbacks should be developed in global fire modules.

scholarly journals Precipitation-fire linkages in Indonesia (1997–2015)

2016 ◽  
Author(s):  
Thierry Fanin ◽  
Guido van der Werf
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Fire Season ◽  
Fire Intensity ◽  
Rainfall Time Series ◽  
Night Time ◽  
Fire Emissions ◽  
Active Fire

Abstract. Over the past decades, fires have burned annually in Indonesia, yet the strength of the fire season is for a large part modulated by the El Niño Southern Oscillation (ENSO). The two most recent very strong El Niño years were 2015 and 1997. Both years involved high incidences of fire in Indonesia. At present, there is no consistent satellite data stream spanning the full 19-year record, thereby complicating a comparison between these two fire seasons. We have investigated how various fire and precipitation datasets can be merged to better compare the fire dynamics in 1997 and 2015 as well as intermediary years. We combined night-time active fire detections from the Along Track Scanning Radiometer (ATSR) World Fire Atlas (WFA) available from 1997 until 2012 and the night-time subset of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor from 2001 until now. For the overlapping period, MODIS detected about 4 times more fires than ATSR, but this ratio varied spatially. Although the reasons behind this spatial variability remain unclear, the temporal correlation for the overlapping period was high (R2 = 0.97) and allowed for a consistent time series. We then constructed a rainfall time series based on the Global Precipitation Climatology Project (GPCP, 1997–2015) and the Tropical Rainfall Measurement Mission Project (TRMM, 1998–2015). Relations between antecedent rainfall and fire activity were not uniform in Indonesia. In southern Sumatra and Kalimantan, we found that 120 days of rainfall accumulation had the highest correlation with annual fire intensity. In northern Sumatra, this period was only 30 days. Thresholds of 200mm and 305mm average rainfall accumulation before each active fire were identified to generate a high fire year in southern Sumatra and southern Kalimantan, respectively. The number of active fires detected in 1997 was 2.2 times higher than in 2015. Assuming the ratio between night-time and total active fires did not change, the 1997 season was thus about twice as fierce as the one in 2015. Although large, the difference is smaller than found in the Global Fire Emissions Database (GFED). Besides different rainfall amounts and patterns, the two-fold difference between 1997 and 2015 may be attributed to a weaker El Niño and neutral IOD conditions in the later year. The fraction of fires burning in peatlands was higher in 2015 compared to 1997 (61 % and 45 %, respectively). Finally, we found that the non-linearity between rainfall and fire in Indonesia stems from longer periods without rain in extremely dry years.

Sources of Subseasonal Skill and Predictability in Wintertime California Precipitation Forecasts

2021 ◽  
Author(s):  
Michelle L. L'Heureux ◽  
Michael K. Tippett ◽  
Emily J. Becker
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Longwave Radiation ◽  
Lead Times ◽  
Strongly Correlated ◽  
Zonal Winds ◽  
Wide Range ◽  
Upper Level ◽  
Tropical Sea

AbstractThe relation between the El Niño-Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal timescales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal timescales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño 3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.

VARIABILIDAD CLIMÁTICA, CAMBIO CLIMÁTICO Y PESQUERÍAS EN EL ECUADOR.

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Current Action ◽  
Palabras Clave

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

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