Figure - available from: Environmental Research Letters
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Changes in the long-term dry season anomalies of key climate variables related to fire weather risk following deforestation: (A) surface temperature and low cloud cover for June–August (jja), (B) surface temperature and low cloud cover for September–November (son), (C) relative humidity and 10 m wind speed for jja and (D) relative humidity and 10 m wind speed for son. The analysis is for the Kalimantan Tengah region which had a reduction in lai > 2 during the dry season (refer to figure 1(c) for changes in lai). Forest and deforestation joint distributions were binned at 10% intervals.
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Deforestation exacerbates climate change through greenhouse gas emissions, but other climatic alterations linked to the local biophysical changes remain poorly understood. Here, we assess the impact of tropical deforestation on fire weather risk – that is the climate conditions conducive to wildfires – using high-resolution convection-permitting cl...
Citations
... We used the Conformal Cubic Atmospheric Model (CCAM; Thatcher, 2020) developed by CSIRO (McGregor, 2005;McGregor & Dix, 2008), to dynamically downscale 15 CMIP6 GCMs. Typically, GCMs are downscaled by running the RCM over a limited domain of interest (Giorgi, 2019), however, CCAM is a global stretched grid model, and so runs for the entire globe, while the domain of interest can be at a higher resolution (McGregor, 2015;Syktus & McAlpine, 2016;Trancoso et al., 2022). In comparison to limited-domain RCMs, a stretched grid model provides self-consistent interactions between global and regional scales (Fox-Rabinovitz et al., 2006). ...
High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 GCMs to a 10 km resolution over Australia using the Conformal Cubic Atmospheric model (CCAM), creating the largest ensemble of high‐resolution downscaled CMIP6 projections for Australia. We compared the host CMIP6 models and downscaled simulations to the Australian Gridded Climate Data (AGCD) observational data and evaluated performance using the Kling‐Gupta efficiency and Perkins skill score. Downscaling improved performance over host GCMs for seasonal temperature and precipitation (10% and 43% respectively), and for annual cycles of temperature and precipitation (6% and 13% respectively). Downscaling also improved the fraction of dry days, reducing the bias for too many low‐rain days. The largest improvements were found in climate extremes, with enhancements to extreme minimum temperatures in all seasons varying from 142% to 201%, and to extreme precipitation of 52% in Austral winter and 47% in summer. The ensemble average integrated skill score improved by 16%. Temperature and precipitation biases were reduced in mountainous and coastal areas. CCAM downscaling outperformed host CMIP6 GCMs at multiple spatial scales and regions—continental Australia, Australian IPCC regions and Queensland's regions—with integrated added value ranging from 9% to 150% and higher over densely populated regions more exposed to climate impacts. This data set will be a valuable resource for understanding future climate changes in Australia.
... Convection-permitting regional pnas.org climate models simulating the impacts of deforestation at a resolution of 4 km are now available (60,61) providing new opportunities to understand the key processes driving the observed temperature response at these scales. ...
Tropical deforestation impacts the climate through complex land–atmosphere interactions causing local and regional warming. However, whilst the impacts of deforestation on local temperature are well understood, the regional (nonlocal) response is poorly quantified. Here, we used remote-sensed observations of forest loss and dry season land–surface temperature during the period 2001 to 2020 to demonstrate that deforestation of the Amazon caused strong warming at distances up to 100 km away from the forest loss. We apply a machine learning approach to show nonlocal warming due to forest loss at 2–100 km length scales increases the warming due to deforestation by more than a factor 4, from 0.16 K to 0.71 K for each 10-percentage points of forest loss. We estimate that rapid future deforestation under a strong inequality scenario could cause dry season warming of 0.96 K across Mato Grosso state in southern Brazil over the period 2020 to 2050. Reducing deforestation could reduce future warming caused by forest loss to 0.4 K. Our results demonstrate the contribution of tropical deforestation to regional climate warming and the potential for reduced deforestation to deliver regional climate adaptation and resilience with important implications for sustainable management of the Amazon.
... This makes oil palm more prone to pest and disease outbreaks, potentially reducing its yields. Other risks include sea-level rise in coastal production areas, especially on peat soils 35 , and increased wildfires 36 . These changes will likely influence interplays between palm oil production and the SDGs and should be modelled specifically to guide sustainable policies. ...
Oil palm ( Elaeis guinensis ) is a controversial crop. To assess its sustainability, we analysed the contribution of different types of plantations (smallholder, industrial and unproductive) towards meeting six Sustainable Development Goals. Using spatial econometric methods and data from 25,067 villages in Sumatra, Indonesia, we revealed that unproductive plantations are associated with more cases of malnutrition, worsened school access, more air pollution and increased criminality. We also proposed a strategy for sustainable palm oil expansion based on replanting unproductive plantations with either industrial or smallholder palm oil. Smallholder replanting was beneficial for five Goals (Zero poverty, Good health, Quality Education, Environmental preservation and Crime reduction), while the same intervention only improved two Goals in the industrial case (Zero poverty and Quality Education). Our appraisal is relevant to policymakers aiming towards the 2030 Agenda, organisations planning oil palm expansion, and retailers or consumers concerned about the sustainability of oil consumption.
... (2) Vegetation is more exposed to human contact and hence ignitions-potential through machinery, smoking, trash burning, etc., proportionately increasing human ignition probability 66,82 (Methods). (3) Fuel moisture and threshold fuel ignition moisture at the patch edge decreases due to edge drying 37-41 , increasing fire risk and propagation potential; (4) Wind infiltration and hence speed at patch edges increases of forests only 81 due to decreased surface roughness 83,84 (Methods, Table 1). Thus, fragmentation potentially decouples fire rate of spread and fire intensity from BA (Figs.1,S2, Methods). ...
Landscape fragmentation has been correlated with either increases or decreases in burned area (BA), but their causal mechanisms remain elusive. Here, road density, a fragmentation proxy, is implemented in a CMIP6 coupled land-fire model, enabling dynamic representation of bottom-up processes affecting fragment edges. Over 2000-2013, fragmentation altered BA by >10% in 16% of burned [0.5°] grid-cells and caused gross changes of -6.5% to +5.5% in global BA. Model output mimicked the global satellite-observed negative relationship between fragmentation and BA, although some regional BA decreases were matched by fire intensity increases. In recently-deforested tropical areas, however, fragmentation drove significant, observationally-consistent increases in BA (~1/4 of Brazilian, Indonesian total BA). Fragmentation BA’s relationship with population density is negative globally-averaged, but hump-shaped and largely positive in tropical and temperate forests. We suggest fragmentation could ‘tip’ toward net BA-amplification with future tropical forest degradation and fire-activity, providing policymakers a first quantification of fragmentation-fire risks.
... These environmental challenges are compounded by ongoing conversion of forested land for farming and modern large-scale agricultural practices. Tropical forests play a key role in regulating regional climate processes and re weather risk, and when cleared for agricultural land leads to a fourfold increase in wild res (Trancoso et al. 2022). Additionally, the modern monocultures of single genetically homogeneous crops that tropical forests are typically cleared for use large quantities of fertilizer and pesticides (Malézieux et al. 2009). ...
Climate change has increased drought and wildfire frequency in recent decades and poses a significant risk to agricultural lands and private property. Given the negative impact of fires on the livelihoods of farmers, it is crucial to assess the flammability of crop species and find ways of mitigating risk of fire in agricultural lands. We quantify the flammability of 66 tropical species of fiber, food, and spice crops by assessing maximum temperature, burn time, and burned biomass and assessed key leaf traits from a subset of these species to look at the interaction of leaf area (LA) and leaf dry matter content (LDMC) with life form type. We found groundcover, shrubs, and vines to be generally less flammable than canopy and subcanopy plants. We also found LDMC to be a consistent and significant predictor of all three flammability measures regardless of plant life form. Our results equips farmers and policy makers with information for constructing more fire resilient agricultural landscapes and pursuing nature-based solutions to mitigate fire risk, such as by planting green firebreaks with fire retardant species.
