scholarly journals Effects of climate variability on savannah fire regimes in West Africa

2015 ◽  
Vol 6 (1) ◽  
pp. 161-174 ◽  
Author(s):  
E. T. N'Datchoh ◽  
A. Konaré ◽  
A. Diedhiou ◽  
A. Diawara ◽  
E. Quansah ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Fire Regimes ◽  
Burned Area ◽  
Climate Conditions ◽  
Burned Areas ◽  
Seasonal Analysis ◽  
Biomass Availability

Abstract. The main objective of this work is to investigate at regional scale the variability in burned areas over the savannahs of West Africa and their links with the rainfall and the large-scale climatic indexes such as the Southern Oscillation Index (SOI), Multivariate ENSO Index (MEI), North Atlantic Oscillation (NAO) and sea surface temperature gradient (SSTG). Daily satellite products (L3JRC) of burned areas from the SPOT Vegetation sensor at a moderate spatial resolution of 1 km x 1 km between 2000 and 2007 were analyzed over the West African savannah in this paper. Results from seasonal analysis revealed a large increase in burned areas from November to February, with consistent peaks in December at the regional scale. In addition, about 30% of the pixels are burned at least four times within the 7-year period. Positive correlations were found between burned areas and rainfall values obtained from the TRMM satellite over savannahs located above 8° N, meaning that a wet rainfall season over these regions was favorable to biomass availability in the next dry season and therefore may induce an increase in burned areas in this region. Moreover, our results showed a nonlinear relationship between the large-scale climatic indexes SOI, MEI, NAO and SSTG and burned-area anomalies. Positive (negative) correlations between burned areas and SOI (MEI) were consistent over the Sahel and Sudano-Sahelian areas. Negative correlations with Atlantic SSTG were significant over the Guinea subregion. Correlations between burned areas over Sudano-Guinean subregion and all the large-scale indexes were weak and may be explained by the fact that this subregion had a mean rainfall greater than 800 mm yr−1 with permanent biomass availability and an optimal amount of soil moisture favorable to fire practice irrespective of the climate conditions. The teleconnection with NAO was not clear and needed to be investigated further.

scholarly journals Effects of climate variability on Savannah fire regimes in West Africa

2012 ◽  
Vol 3 (2) ◽  
pp. 1021-1053 ◽  
Author(s):  
E. T. N'Datchoh ◽  
A. Konaré ◽  
A. Diedhiou ◽  
P. Assamoi
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Fire Regimes ◽  
Time Variability ◽  
Climatic Impact ◽  
Burned Areas ◽  
Environmental Processes ◽  
The North ◽  
Annual Scale

Abstract. Bushfires are recognized as environmental processes that affect the atmosphere by the gases and particles emitted and have an ecological and climatic impact. However, there are still numerous uncertainties, particularly about the variability of fire occurrence on the intra- and inter-annual scale. Our objective was to distinguish the space-time variability of fires in West Africa through analysis of burned areas using SPOT VEGETATION from L3JRC (1 April 2000 to 31 March 2007) which were obtained from the modification in the algorithm of cells from the GBA 2000 project. We also analyzed the influence of several large scale factors such as the ENSO, SOI, NAO and the north-south Atlantic temperature gradient factor (SSTG) on the variability of the span of burned areas. Based on areas burned monthly, we calculated the frequency of fire passage on the same pixel. This helped characterize the activity of pixels and distinguish the most vulnerable zones (with a lot of fire activity) from the least vulnerable ones (with less activity). Using a correlation calculation, we also found the influence of the quality of precipitations during preceding rainy seasons on burned areas during the dry season along with climate factors such as MEI, SOI, NAO and the SSTG.

Analysis of Mean Climate Conditions in Senegal (1971–98)

2006 ◽  
Vol 10 (5) ◽  
pp. 1-40 ◽  
Author(s):  
Souleymane Fall ◽  
Dev Niyogi ◽  
Fredrick H. M. Semazzi
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Regional Climate ◽  
Linear Regression Analysis ◽  
Regional Scale ◽  
Regional Climate Change ◽  
Warming Trend ◽  
Positive Trend ◽  
Local Climate ◽  
Climate Conditions

Abstract This paper presents a GIS-based analysis of climate variability over Senegal, West Africa. It responds to the need for developing a climate atlas that uses local observations instead of gridded global analyses. Monthly readings of observed rainfall (20 stations) and mean temperature (12 stations) were compiled, digitized, and quality assured for a period from 1971 to 1998. The monthly, seasonal, and annual temperature and precipitation distributions were mapped and analyzed using ArcGIS Spatial Analyst. A north–south gradient in rainfall and an east–west gradient in temperature variations were observed. June exhibits the greatest variability for both quantity of rainfall and number of rainy days, especially in the western and northern parts of the country. Trends in precipitation and temperature were studied using a linear regression analysis and interpolation maps. Air temperature showed a positive and significant warming trend throughout the country, except in the southeast. A significant correlation is found between the temperature index for Senegal and the Pacific sea surface temperatures during the January–April period, especially in the El Niño zone. In contrast to earlier regional-scale studies, precipitation does not show a negative trend and has remained largely unchanged, with a few locations showing a positive trend, particularly in the northeastern and southwestern regions. This study reveals a need for more localized climate analyses of the West Africa region because local climate variations are not always captured by large-scale analysis, and such variations can alter conclusions related to regional climate change.

scholarly journals Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

2021 ◽  
Vol 13 (8) ◽  
pp. 1509
Author(s):  
Xikun Hu ◽  
Yifang Ban ◽  
Andrea Nascetti
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Multiple Scales ◽  
Detection Methods ◽  
Burned Area ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Burned Areas ◽  
Local Climate Zones ◽  
Sentinel 2

Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery. Specifically, several semantic segmentation network architectures, i.e., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. The validation results show that the DL algorithms outperform the ML methods in two of the three cases with the compact burned scars, while ML methods seem to be more suitable for mapping dispersed burn in boreal forests. Using Sentinel-2 images, U-Net and HRNet exhibit comparatively identical performance with higher kappa (around 0.9) in one heterogeneous Mediterranean fire site in Greece; Fast-SCNN performs better than others with kappa over 0.79 in one compact boreal forest fire with various burn severity in Sweden. Furthermore, directly transferring the trained models to corresponding Landsat-8 data, HRNet dominates in the three test sites among DL models and can preserve the high accuracy. The results demonstrated that DL models can make full use of contextual information and capture spatial details in multiple scales from fire-sensitive spectral bands to map burned areas. Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard processing in the next Earth observation satellites.

scholarly journals Holocene changes in African vegetation: tradeoff between climate and water availability

2014 ◽  
Vol 10 (2) ◽  
pp. 681-686 ◽  
Author(s):  
C. Hély ◽  
A.-M. Lézine ◽  
APD contributors
Keyword(s):  
West Africa ◽  
Water Availability ◽  
Regional Scale ◽  
Plant Distribution ◽  
Climate Conditions ◽  
Tropical Plants ◽  
Plant Migration ◽  
Spatio Temporal ◽  
The Individual ◽  
Instrumental Records

Abstract. Although past climate change is well documented in West Africa through instrumental records, modeling activities, and paleo-data, little is known about regional-scale ecosystem vulnerability and long-term impacts of climate on plant distribution and biodiversity. Here we use paleohydrological and paleobotanical data to discuss the relation between available surface water, monsoon rainfall and vegetation distribution in West Africa during the Holocene. The individual patterns of plant migration or community shifts in latitude are explained by differences among tolerance limits of species to rainfall amount and seasonality. Using the probability density function methodology, we show here that the widespread development of lakes, wetlands and rivers at the time of the "Green Sahara" played an additional role in forming a network of topographically defined water availability, allowing for tropical plants to migrate north from 15 to 24° N (reached ca. 9 cal ka BP). The analysis of the spatio–temporal changes in biodiversity, through both pollen occurrence and richness, shows that the core of the tropical rainbelt associated with the Intertropical Convergence Zone was centered at 15–20° N during the early Holocene wet period, with comparatively drier/more seasonal climate conditions south of 15° N.

scholarly journals Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

2021 ◽  
Author(s):  
Iñigo Gómara ◽  
Belén Rodríguez-Fonseca ◽  
Elsa Mohino ◽  
Teresa Losada ◽  
Irene Polo ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Marine Ecosystem ◽  
Ecosystem Model ◽  
Tropical Pacific ◽  
Equatorial Atlantic ◽  
Climate Conditions ◽  
Marine Food Web ◽  
Marine Ecosystem Model ◽  
The Tropical Pacific

AbstractTropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.

The influence of termite-induced heterogeneity on savanna vegetation along a climatic gradient in West Africa

2012 ◽  
Vol 29 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Arne Erpenbach ◽  
Markus Bernhardt-Römermann ◽  
Rüdiger Wittig ◽  
Adjima Thiombiano ◽  
Karen Hahn
Keyword(s):  
West Africa ◽  
Plant Species ◽  
Large Scale ◽  
Regional Scale ◽  
Soil Conditions ◽  
Soil Parameters ◽  
Climatic Gradient ◽  
Termite Mound ◽  
Savanna Vegetation ◽  
Bioclimatic Variables

Abstract:Termites are renowned ecosystem engineers. Their mounds have been described as an important element of savanna vegetation dynamics, but little is known about their large-scale impact on vegetation composition. To investigate the influence of termite-induced heterogeneity in savannas along a climatic gradient in West Africa termite mound vegetation was compared with adjacent savanna vegetation using 256 paired plots (size of the termite mound and a corresponding savanna area) in five protected areas from northern Burkina Faso to northern Benin. On each plot vegetation and soil sampling was performed. Additionally bioclimatic variables from the WORLDCLIM database were used. The vegetation on the mounds and the surrounding savanna differed within all study sites (DCA length of gradient 3.85 SD) and showed complete turnover along the climatic gradient (DCA length of gradient 5.99 SD). Differences between mounds and savanna were significantly related to termite-induced changes in soil parameters, specifically clay enrichment and increased cation concentrations (base saturation). On a local scale, termite-induced differences in soil conditions were found to be the most important factor affecting mound vegetation, while on a regional scale, annual precipitation showed the strongest significant correlations. However, with increasing precipitation, differences between mounds and the surrounding matrix became more pronounced, and the contribution of mounds to local phytodiversity increased. Eleven plant species were identified as characteristic termite mound species. In the more humid parts of the gradient, more characteristic plant species were found that may benefit from favourable soil conditions, good water availability, and a low fire impact in the mound microhabitat.

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>

Fire spread from MODIS burned area data: obtaining fire dynamics information for every single fire

2016 ◽  
Vol 25 (12) ◽  
pp. 1228 ◽  
Author(s):  
David Frantz ◽  
Marion Stellmes ◽  
Achim Röder ◽  
Joachim Hill
Keyword(s):  
Large Scale ◽  
Fire Regimes ◽  
Fire Spread ◽  
Burned Area ◽  
Large Area ◽  
Fire Dynamics ◽  
Seed Point ◽  
Individual Object ◽  
The Individual ◽  
Area Data

Fire spread information on a large scale is still a missing key layer for a complete description of fire regimes. We developed a novel multilevel object-based methodology that extracts valuable information about fire dynamics from Moderate Resolution Imaging Spectroradiometer (MODIS) burned area data. Besides the large area capabilities, this approach also derives very detailed information for every single fire regarding timing and location of its ignition, as well as detailed directional multitemporal spread information. The approach is a top–down approach and a multilevel segmentation strategy is used to gradually refine the individual object membership. The multitemporal segmentation alternates between recursive seed point identification and queue-based fire tracking. The algorithm relies on only a few input parameters that control the segmentation with spatial and temporal distance thresholds. We present exemplary results that indicate the potential for further use of the derived parameters.

scholarly journals Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

2021 ◽  
Vol 13 (23) ◽  
pp. 4730
Author(s):  
Malak Henchiri ◽  
Tertsea Igbawua ◽  
Tehseen Javed ◽  
Yun Bai ◽  
Sha Zhang ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Joint Probability ◽  
Meteorological Drought ◽  
Socioeconomic Impacts ◽  
The North ◽  
The Standardized Precipitation Index ◽  
The North Atlantic Oscillation

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.

Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

2021 ◽  
Author(s):  
Iñigo Gómara ◽  
Belén Rodríguez-Fonseca ◽  
Elsa Mohino ◽  
Teresa Losada ◽  
Irene Polo ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Marine Ecosystem ◽  
Ecosystem Model ◽  
Tropical Pacific ◽  
Equatorial Atlantic ◽  
Climate Conditions ◽  
Marine Food Web ◽  
Marine Ecosystem Model ◽  
The Tropical Pacific

<p>Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.</p>

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